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SciRIFF

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You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The powerful mechanism of lexical rules (Carpenter 1991) has been used in many natural language processing systems. Citation Sentence: The powerful mechanism of lexical rules ( Carpenter 1991 ) has been used in many natural language processing systems . Context after the citation: In this section we briefly discuss some of the more prominent approaches and compare them with the treatment proposed in this paper.

Background

acl_arc_intent_classification:train:1178

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: The version proposed here combines a basic insight from Lewin (1990) with higher-order unification to give an analysis that has a strong resemblance to that proposed in Pereira (1990, 1991), with some differences that are commented on below. We can implement a deductive theory of quantifier scope using the conditional equivalence mechanism. Citation Sentence: The version proposed here combines a basic insight from Lewin ( 1990 ) with higher-order unification to give an analysis that has a strong resemblance to that proposed in Pereira ( 1990 , 1991 ) , with some differences that are commented on below . Context after the citation: Like Pereira's approach, it avoids the need for a free variable constraint, nor does it need the explicit recursion on the quantifier restriction imposed by Lewin. We analyze quantified NPs at the QLF level as illustrated in the QLF for: (19) Every manager uses a computer. ex istsl ( e. pos( pres( u se(e,eve ry( m a na ger), a c.,„„(com put er))))

CompareOrContrast

acl_arc_intent_classification:train:1179

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: • Only an automatic evaluation was performed, which relied on having model responses (Berger and Mittal 2000; Berger et al. 2000). • Only qualitative observations of the responses were reported (no formal evaluation was performed) (Lapalme and Kosseim 2003; Roy and Subramaniam 2006). These systems addressed the evaluation issue as follows. Citation Sentence: • Only an automatic evaluation was performed , which relied on having model responses ( Berger and Mittal 2000 ; Berger et al. 2000 ) . Context after the citation: • A user study was performed, but it was either very small compared to the corpus (Carmel, Shtalhaim, and Soffer 2000; Jijkoun and de Rijke 2005), or the corpus itself was significantly smaller than ours (Feng et al. 2006; Leuski et al. 2006). The representativeness of the sample size was not discussed in any of these studies. There are significant practical difficulties associated with conducting the user studies needed to produce meaningful results for our system. Firstly, the size of our corpus and the number of parameters and settings that we need to test mean that in order for a user study to be representative, a fairly large sample involving several hundreds of request–response pairs would have to be used.

CompareOrContrast

acl_arc_intent_classification:train:118

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Liang et al. (2006) presented a perceptron-based algorithm for learning the phrase-translation parameters in a statistical machine translation system. Furthermore, we also evaluate the method on alternate extrinsic loss functions. This allows us to give guarantees of convergence. Citation Sentence: Liang et al. ( 2006 ) presented a perceptron-based algorithm for learning the phrase-translation parameters in a statistical machine translation system . Context after the citation: Similar to the inline-ranker loss function presented here, they use a k-best lists of hypotheses in order to identify parameters which can improve a global objective function: BLEU score. In their work, they are interested in learning a parameterization over translation phrases (including the underlying wordalignment) which optimizes the BLEU score. Their goal is considerably different; they want to incorporate additional features into their model and define an objective function which allows them to do so; whereas, we are interested in allowing for multiple objective functions in order to adapt the parser model parameters to downstream tasks or alternative intrinsic (parsing) objectives. The work that is most similar to ours is that of Chang et al. (2007), who introduced the Constraint Driven Learning algorithm (CODL).

CompareOrContrast

acl_arc_intent_classification:train:1180

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: NLG has to do more than select a distinguishing description (i.e., one that unambiguously denotes its referent; Dale 1989): The selected expression should also be felicitous. Citation Sentence: NLG has to do more than select a distinguishing description ( i.e. , one that unambiguously denotes its referent ; Dale 1989 ) : The selected expression should also be felicitous . Context after the citation: Consider the question, discussed in the philosophical logic literature, of whether it is legitimate, for a gradable adjective, to distinguish between “observationally indifferent” entities: Suppose two objects x and y, are so similar that it is impossible to distinguish their sizes; can it ever be reasonable to say that x is large and y is not? A positive answer would not be psychologically plausible, since x and y are indistinguishable; but a negative answer would prohibit any binary distinction between objects that are large and objects that are not, given that one can always construct objects x and y, one of which falls just below the divide while the other falls just above it. This is the strongest version of the sorites paradox (e.g., Hyde 2002). Our approach to vague descriptions allows a subtle response: that the offending statement may be correct yet infelicitous.

Background

acl_arc_intent_classification:train:1181

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Juola (1994, 1997) conducts some small experiments using his METLA system to show the viability of this approach for English −> French and English −> Urdu. Given that the marker hypothesis is arguably universal, it is clear that benefits may accrue by using it to facilitate subsentential alignment of (source, target) chunks. Citation Sentence: Juola ( 1994 , 1997 ) conducts some small experiments using his METLA system to show the viability of this approach for English − > French and English − > Urdu . Context after the citation: For the English −> French language pair, Juola gives results of 61% correct translation when the system is tested on the training corpus, and 36% accuracy when it is evaluated with test data. For English −> Urdu, Juola (1997, page 213) notes that “the system learned the original training corpus ... perfectly and could reproduce it without errors”; that is, it scored 100% accuracy when tested against the training corpus. On novel test sentences, he gives results of 72% correct translation. In their Gaijin system, Veale and Way (1997) give a result of 63% accurate translations obtained for English −> German on a test set of 791 sentences from CorelDRAW manuals.

Background

acl_arc_intent_classification:train:1182

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: This idea of preserving properties can be considered an instance of the well-known frame problem in AT (McCarthy and Hayes 1969), and we will therefore refer to the specifications left implicit by the linguist as the frame specification, or simply frame, of a lexical rule. (Pollard and Sag [1994, 3141, following Flickinger [19871). This is so since the lexical rule in Figure 2 "(like all lexical rules in HPSG) preserves all properties of the input not mentioned in the rule." Citation Sentence: This idea of preserving properties can be considered an instance of the well-known frame problem in AT ( McCarthy and Hayes 1969 ) , and we will therefore refer to the specifications left implicit by the linguist as the frame specification , or simply frame , of a lexical rule . Context after the citation: Not having to represent the frame explicitly not only enables the linguist to express only the relevant things, but also allows a more compact representation of lexical rules where explicit framing would require the rules to be split up (Meurers 1994). One thus needs to distinguish the lexical rule specification provided by the linguist from the fully explicit lexical rule relations integrated into the theory. The formalization of DLRs provided by Meurers (1995) defines a formal lexical rule specification language and provides a semantics for that language in two steps: A rewrite system enriches the lexical rule specification into a fully explicit description of the kind shown in Figure 1. This description can then be given the standard set-theoretical interpretation of King (1989, 1994).'

CompareOrContrast

acl_arc_intent_classification:train:1183

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: All experiments have been performed using MaltParser (Nivre et al., 2006), version 0.4, which is made available together with the suite of programs used for preand post-processing.1 • Graph transformations for recovering nonprojective structures (Nivre and Nilsson, 2005). • Support vector machines for mapping histories to parser actions (Kudo and Matsumoto, 2002). Citation Sentence: All experiments have been performed using MaltParser ( Nivre et al. , 2006 ) , version 0.4 , which is made available together with the suite of programs used for preand post-processing .1 Context after the citation: 1www. msi.vxu.se/users/nivre/research/MaltParser.html

Uses

acl_arc_intent_classification:train:1184

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: One area of current interest concerns the left-to-right arrangement of premodifying adjectives within an NP (e.g., Shaw and Hatzivassiloglou 1999; Malouf 2000). A realization phase, during which the choice between base, superlative, and comparative forms is made, among other things. An inference phase, during which the list L is transformed; 3. Citation Sentence: One area of current interest concerns the left-to-right arrangement of premodifying adjectives within an NP ( e.g. , Shaw and Hatzivassiloglou 1999 ; Malouf 2000 ) . Context after the citation: Work in this area is often based on assigning adjectives to a small number of categories (e.g., Precentral, Central, Postcentral, and Prehead), which predict adjectives’ relative position. Interestingly, vague properties tend to be realized before others. Quirk et al. (1985), for example, report that “adjectives denoting size, length, and height normally precede other nonderived adjectives” (e.g., the small round table is usually preferred to the round small table). Semantically, this does not come as a surprise.

Background

acl_arc_intent_classification:train:1185

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: Better results would be expected by combining the PCFG-LA parser with discriminative reranking approaches (Charniak and Johnson, 2005; Huang, 2008) for self training. We conjecture based on our analysis that the EM training algorithm is able to exploit the information available in both gold and automatically labeled data with more complex grammars while being less affected by over-fitting. We show for the first time that self-training is able to significantly improve the performance of a PCFG-LA parser, a single generative parser, on both small and large amounts of labeled training data. Citation Sentence: Better results would be expected by combining the PCFG-LA parser with discriminative reranking approaches ( Charniak and Johnson , 2005 ; Huang , 2008 ) for self training . Context after the citation: Self-training should also benefit other discriminatively trained parsers with latent annotations (Petrov and Klein, 2008), although training would be much slower compared to using generative models, as in our case. In future work, we plan to scale up the training process with more unlabeled training data (e.g., gigaword) and investigate automatic selection of materials that are most suitable for self-training. We also plan to investigate domain adaptation and apply the model to other languages with modest treebank resources. Finally, it is also important to explore other ways to exploit the use of unlabeled data.

FutureWork

acl_arc_intent_classification:train:1186

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Some researchers (Cucerzan, 2007; Nguyen and Cao, 2008) have explored the use of Wikipedia information to improve the disambiguation process. Other representations use the link structure (Malin, 2005) or generate graph representations of the extracted features (Kalashnikov et al., 2007). Nevertheless, the full document text is present in most systems, sometimes as the only feature (Sugiyama and Okumura, 2007) and sometimes in combination with others see for instance (Chen and Martin, 2007; Popescu and Magnini, 2007)-. Citation Sentence: Some researchers ( Cucerzan , 2007 ; Nguyen and Cao , 2008 ) have explored the use of Wikipedia information to improve the disambiguation process . Context after the citation: Wikipedia provides candidate entities that are linked to specific mentions in a text. The obvious limitation of this approach is that only celebrities and historical figures can be identified in this way. These approaches are yet to be applied to the specific task of grouping search results. Biographical features are strongly related to NEs and have also been proposed for this task due to its high precision.

Background

acl_arc_intent_classification:train:1187

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Others have applied the NLP technologies of near-duplicate detection and topic-based text categorization to politically oriented text (Yang and Callan, 2005; Purpura and Hillard, 2006). An exception is Grefenstette et al. (2004), who experimented with determining the political orientation of websites essentially by classifying the concatenation of all the documents found on that site. There has also been work focused upon determining the political leaning (e.g., “liberal” vs. “conservative”) of a document or author, where most previously-proposed methods make no direct use of relationships between the documents to be classified (the “unlabeled” texts) (Laver et al., 2003; Efron, 2004; Mullen and Malouf, 2006). Citation Sentence: Others have applied the NLP technologies of near-duplicate detection and topic-based text categorization to politically oriented text ( Yang and Callan , 2005 ; Purpura and Hillard , 2006 ) . Context after the citation: Detecting agreement We used a simple method to learn to identify cross-speaker references indicating agreement. More sophisticated approaches have been proposed (Hillard et al., 2003), including an extension that, in an interesting reversal of our problem, makes use of sentimentpolarity indicators within speech segments (Galley et al., 2004). Also relevant is work on the general problems of dialog-act tagging (Stolcke et al., 2000), citation analysis (Lehnert et al., 1990), and computational rhetorical analysis (Marcu, 2000; Teufel and Moens, 2002). We currently do not have an efficient means to encode disagreement information as hard constraints; we plan to investigate incorporating such information in future work.

Background

acl_arc_intent_classification:train:1188

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: We chose to follow Ng and Low (2004) and split the sentences evenly to facilitate further comparison. Shi and Wang (2007) also chunked the sentences before doing 10-fold cross validation, but used an uneven split. However, the comparison is indirect because our partitions of the CTB corpus are different. Citation Sentence: We chose to follow Ng and Low ( 2004 ) and split the sentences evenly to facilitate further comparison . Context after the citation: Compared with Ng and Low (2004), our baseline model gave slightly better accuracy, consistent with our previous observations about the word segmentors (Zhang and Clark, 2007). Due to the large accuracy gain from the baseline, our joint model performed much better. In summary, when compared with existing joint word segmentation and POS tagging systems in the literature, our proposed model achieved the best accuracy boost from the cascaded baseline, and competent overall accuracy.

Uses

acl_arc_intent_classification:train:1189

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: In comparison, the tag set of the Buckwalter Morphological Analyzer (Buckwalter 2004) used in the PATB has a core POS set of 44 tags (CORE44) before morphological extension.8 Cross-linguistically, a core set containing around 12 tags is often Traditional Arabic grammars often describe a very general three-way distinction into verbs, nominals, and particles. Linguistically, words have associated POS tags, e.g., “verb” or “noun,” which further abstract over morphologically and syntactically similar lexemes. Citation Sentence: In comparison , the tag set of the Buckwalter Morphological Analyzer ( Buckwalter 2004 ) used in the PATB has a core POS set of 44 tags ( CORE44 ) before morphological extension .8 Cross-linguistically , a core set containing around 12 tags is often Context after the citation: 7 We ignore the rare “false idafa” construction (Habash 2010, p. 102). 8 The 44 tags in CORE44 are based on the tokenized version of Arabic words. There are 34 untokenized core tags as used in MADA+TOKAN (Habash, Rambow, and Roth 2012). assumed as a “universal tag set” (Rambow et al. 2006; Petrov, Das, and McDonald 2012).

CompareOrContrast

acl_arc_intent_classification:train:119

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: That is, a document that contains terms al, a2 and a3 may be ranked higher than a document which contains terms al and b.f. However, the second document is more likely to be relevant since correct translations of the query terms are more likely to co-occur (Ballesteros and Croft, 1998). Also, a document matching different translations of one term in the original query may be ranked higher than a document that matches translations of different terms in the original query. Since all terms are treated as equal in the translated query, this gives terms with more translations (potentially the more common terms) more credit in retrieval, even though such terms should potentially be given less credit if they are more common. Citation Sentence: That is , a document that contains terms al , a2 and a3 may be ranked higher than a document which contains terms al and b.f. However , the second document is more likely to be relevant since correct translations of the query terms are more likely to co-occur ( Ballesteros and Croft , 1998 ) . Context after the citation: A second method is to structure the translated query, separating the translations for one term from translations for other terms. This approach limits how much credit the retrieval algorithm can give to a single term in the original query and prevents the translations of one or a few terms from swamping the whole query. There are several variations of such a method (Ballesteros and Croft, 1998; Pirkola, 1998; Hull 1997). One such method is to treat different translations of the same term as synonyms.

Background

acl_arc_intent_classification:train:1190

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: The last years have seen considerable advances in the field of anaphora resolution, but a number of outstanding issues either remain unsolved or need more attention and, as a consequence, represent major challenges to the further development of the field (Mitkov 2001a). Instead of defining a total preference ordering, Kibble argues that a partial ordering emerges from the interaction among cohesion (maintaining the same center), salience (realizing the center as subject), and cheapness (realizing the anticipated center of a following utterance as subject). Finally, in his squib Kibble discusses a reformulation of the centering transitions (Continue, Retain, and Shift), which specify the center movement across sentences. Citation Sentence: The last years have seen considerable advances in the field of anaphora resolution , but a number of outstanding issues either remain unsolved or need more attention and , as a consequence , represent major challenges to the further development of the field ( Mitkov 2001a ) . Context after the citation: A fundamental question that needs further investigation is how far the performance of anaphora resolution algorithms can go and what the limitations of knowledge-poor methods are. In particular, more research should be carried out on the factors influencing the performance of these algorithms. One of the impediments to the evaluation or fuller utilization of machine learning techniques is the lack of widely available corpora annotated for anaphoric or coreferential links. More work toward the proposal of consistent and comprehensive evaluation is necessary; so too is work in multilingual contexts.

FutureWork

acl_arc_intent_classification:train:1191

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Using an accumulator passing technique (O'Keefe 1990), we ensure that upon execution of a call to the interaction predicate q_1 a new lexical entry is derived as the result of successive application of a number of lexical rules. Each transition in the automaton is translated into a definite relation in which the corresponding lexical rule predicate is called, and each final state is encoded by a unit clause. In fact, one can view the representations as notational variants of one another. Citation Sentence: Using an accumulator passing technique ( O'Keefe 1990 ) , we ensure that upon execution of a call to the interaction predicate q_1 a new lexical entry is derived as the result of successive application of a number of lexical rules . Context after the citation: Because of the word class specialization step discussed in Section 3.3, the execution avoids trying out many lexical rule applications that are guaranteed to fail. We illustrate the encoding with the finite-state automaton of Figure 16. As the lexical rules themselves are already translated into a definite clause representation in the first compilation step, the interaction predicates only need to ensure that the right combination of lexical rule predicates is called. The interaction predicate encoding the finite-state automaton of Figure 16 is shown in Figure 18.28 We now have a first complete encoding of the lexical rules and their interaction represented as covariation in lexical entries.

Uses

acl_arc_intent_classification:train:1192

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: However, most strategies are based on "internal" or "external methods" (Grabar and Zweigenbaum, 2002), i.e. methods that rely on the form of terms or on the information gathered from contexts. Different strategies have been developed in order to identify pairs of terms that share a specific semantic relationship (such as hyperonymy or meronymy) or to build classes of terms. Recent literature in computational terminology has shown an increasing interest in identifying various semantic relationships between terms. Citation Sentence: However , most strategies are based on `` internal '' or `` external methods '' ( Grabar and Zweigenbaum , 2002 ) , i.e. methods that rely on the form of terms or on the information gathered from contexts . Context after the citation: (In some cases, an additional resource, such as a dictionary or a thesaurus, is used during the identification process.) The work reported here infers specific semantic relationships based on sets of examples and counterexamples. In this paper, the method is applied to a French corpus on computing to find noun-verb combinations in which verbs convey a meaning of realization. The work is carried out in order to assist terminographers in the enrichment of a dictionary on computing that includes collocational information (L'Homme, 2004).

CompareOrContrast

acl_arc_intent_classification:train:1193

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: With the exception of (Fung, 1995b), previous methods for automatically constructing statistical translation models begin by looking at word cooccurrence frequencies in bitexts (Gale & Church, 1991; Kumano & Hirakawa, 1994; Fung, 1995a; Melamed, 1995). 2 Co-occurrence The hidden parameters can be conditioned on prior knowledge about the bitext to improve the model's accuracy. Citation Sentence: With the exception of ( Fung , 1995b ) , previous methods for automatically constructing statistical translation models begin by looking at word cooccurrence frequencies in bitexts ( Gale & Church , 1991 ; Kumano & Hirakawa , 1994 ; Fung , 1995a ; Melamed , 1995 ) . Context after the citation: A bitext comprises a pair of texts in two languages, where each text is a translation of the other. Word co-occurrence can be defined in various ways. The most common way is to divide each half of the bitext into an equal number of segments and to align the segments so that each pair of segments Si and Ti are translations of each other (Gale & Church, 1991; Melamed, 1996a). Then, two word tokens (u, v) are said to co-occur in the

Background

acl_arc_intent_classification:train:1194

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: A substring in the sentence that corresponds to a node in the representation tree is denoted by assigning the interval of the substring to SNODE of 2 These definitions are based on the discussion in (Tang, 1994) and Boitet & Zaharin (1988). An interval is assigned to each word in the sentence, i.e. (0-1) for “John”, (1-2) for “picks”, (2-3) for “the", (3-4) for “box” and (4-5) for “up”. It contains a nonprojective correspondence. Citation Sentence: A substring in the sentence that corresponds to a node in the representation tree is denoted by assigning the interval of the substring to SNODE of 2 These definitions are based on the discussion in ( Tang , 1994 ) and Boitet & Zaharin ( 1988 ) . Context after the citation: the node, e.g. the node “picks up” with SNODE intervals (1-2+4-5) corresponds to the words “picks” and "up" in the string with the similar intervals.The correspondence between subtrees and substrings are denoted by the interval assigned to the STREE of each node, e.g. the subtree rooted at node “picks up” with STREE interval (0-5) corresponds to the whole sentence “John picks the box up”. The case depicted in Figure 2, describes how the SSTC structure treats some non-standard linguistic phenomena. The particle "up" is featurised into the verb "pick" and in discontinuous manner (e.g. "up" (4-5) in "pick-up" (1-2+4-5)) in the sentence "He picks the box up". For more details on the proprieties of SSTC, see Boitet & Zaharin (1988).

Uses

acl_arc_intent_classification:train:1195

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: The Web People Search task, as defined in the first WePS evaluation campaign (Artiles et al., 2007), consists of grouping search results for a given name according to the different people that share it. In some cases, the existence of a predominant person (such as a celebrity or a historical figure) makes it likely to dominate the ranking of search results, complicating the task of finding information about other people sharing her name. The user might refine the original query with additional terms, but this risks excluding relevant documents in the process. Citation Sentence: The Web People Search task , as defined in the first WePS evaluation campaign ( Artiles et al. , 2007 ) , consists of grouping search results for a given name according to the different people that share it . Context after the citation: Our goal in this paper is to study which document features can contribute to this task, and in particular to find out which is the role that can be played by named entities (NEs): (i) How reliable is NEs overlap between documents as a source of evidence to cluster pages? (ii) How much recall does it provide? (iii) How unique is this signal? (i.e. is it redundant with other sources of information such as n-gram overlap?)

Background

acl_arc_intent_classification:train:1196

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: Although this is only true in cases where y occurs in an upward monotone context (MacCartney and Manning, 2007), in practice genuine contradictions between y-values sharing a meronym relationship are extremely rare. For example, in the set born in(Mozart,•) there is no contradiction between the y values “Salzburg” and “Austria”, but “Salzburg” conflicts with “Vienna”. Meronyms: For some relations, there is no contradiction when y1 and y2 share a meronym, i.e. “part of” relation. Citation Sentence: Although this is only true in cases where y occurs in an upward monotone context ( MacCartney and Manning , 2007 ) , in practice genuine contradictions between y-values sharing a meronym relationship are extremely rare . Context after the citation: We therefore simply assigned contradictions between meronyms a probability close to zero. We used the Tipster Gazetteer4 and WordNet to identify meronyms, both of which have high precision but low coverage. Argument Typing: Two y values are not contradictory if they are of different argument types. For example, the relation born in can take a date or a location for the y value.

Motivation

acl_arc_intent_classification:train:1197

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: We use the same data setting with Xue (2008), however a bit different from Xue and Palmer (2005). The test set includes 72 files, which are chtb_001 to chtb_041, and chtb_900 to chtb_931. fid. Citation Sentence: We use the same data setting with Xue ( 2008 ) , however a bit different from Xue and Palmer ( 2005 ) . Context after the citation:

Uses

acl_arc_intent_classification:train:1198

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Erk (2007) compared a number of techniques for creating similar-word sets and found that both the Jaccard coefficient and Lin (1998a)’s information-theoretic metric work best. One key issue is how to define the set of similar words, SIMS(w). In contrast, Erk (2007) generalizes by substituting similar arguments, while Wang et al. (2005) use the cross-product of similar pairs. Citation Sentence: Erk ( 2007 ) compared a number of techniques for creating similar-word sets and found that both the Jaccard coefficient and Lin ( 1998a ) 's information-theoretic metric work best . Context after the citation: Similarity-smoothed models are simple to compute, potentially adaptable to new domains, and require no manually-compiled resources such as WordNet. Selectional Preferences have also been a recent focus of researchers investigating the learning of paraphrases and inference rules (Pantel et al., 2007; Roberto et al., 2007). Inferences such as “[X wins Y] ⇒ [X plays Y]” are only valid for certain arguments X and Y. We follow Pantel et al. (2007) in using automatically-extracted semantic classes to help characterize plausible arguments.

Background

acl_arc_intent_classification:train:1199

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The extraction procedure consists of three steps: First, the bracketing of the trees in the Penn Treebank is corrected and extended based on the approaches of Magerman (1994) and Collins (1997). Xia (1999) also presents a similar method for the extraction of a TAG from the Penn Treebank. The number of frame types extracted (i.e., an elementary tree without a specific lexical anchor) ranged from 2,366 to 8,996. Citation Sentence: The extraction procedure consists of three steps : First , the bracketing of the trees in the Penn Treebank is corrected and extended based on the approaches of Magerman ( 1994 ) and Collins ( 1997 ) . Context after the citation: Then the elementary trees are read off in a quite straightforward manner. Finally any invalid elementary trees produced as a result of annotation errors in the treebank are filtered out using linguistic heuristics. The number of frame types extracted by Xia (1999) ranged from 3,014 to 6,099. Hockenmaier, Bierner, and Baldridge (2004) outline a method for the automatic extraction of a large syntactic CCG lexicon from the Penn-II Treebank.

Background

acl_arc_intent_classification:train:12

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: • use of low level knowledge from the speech recognition phase, • use of high level knowledge about the domain in particular and the dialogue task in general, • a "continue" facility and an "auto-loop" facility as described by Biermann and Krishnaswamy (1976), • a "conditioning" facility as described by Fink et al. (1985), • implementation of new types of paraphrasing, • checking a larger environment in the expectation acquisition algorithm when deciding if an incoming sentence is the same or similar to one already seen, and • examining inter-speaker dialogue patterns. These include the following: However, there are many possible extensions that could be examined in the future and added to the implementation if the investigation indicates that it would create a yet more usable system. Citation Sentence: • use of low level knowledge from the speech recognition phase , • use of high level knowledge about the domain in particular and the dialogue task in general , • a `` continue '' facility and an `` auto-loop '' facility as described by Biermann and Krishnaswamy ( 1976 ) , • a `` conditioning '' facility as described by Fink et al. ( 1985 ) , • implementation of new types of paraphrasing , • checking a larger environment in the expectation acquisition algorithm when deciding if an incoming sentence is the same or similar to one already seen , and • examining inter-speaker dialogue patterns . Context after the citation: All but two of these areas for expansion are aimed at moving the expectation system from one that finds patterns in a user's dialogues and acquires historical knowledge about them to one that can acquire true procedures. The first two areas for expansion have nothing to do with creating a true procedure acquisition module but would be highly desirable from the point of view of the speech recognition application. Features three and four would simply make the system easier to use and would require little theoretical investigation. The final three would require research efforts.

FutureWork

acl_arc_intent_classification:train:120

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: We previously showed that incorporating this intuition into a Bayesian prior can help train a CCG supertagger (Garrette et al., 2014). Baldridge further notes that due to the natural associativity of CCG, adjacent categories tend to be combinable. pler categories by encoding a notion of category simplicity into a prior (Garrette et al., 2015). Citation Sentence: We previously showed that incorporating this intuition into a Bayesian prior can help train a CCG supertagger ( Garrette et al. , 2014 ) . Context after the citation: In this paper, we present a novel parsing model that is designed specifically for the capacity to capture both of these universal, intrinsic properties of CCG. We do so by extending our previous, PCFG-based parsing model to include parameters that govern the relationship between constituent categories and the preterminal categories (also known as supertags) to the left and right. The advantage of modeling context within a CCG framework is that while CCM must learn which contexts are likely purely from the data, the CCG categories give us obvious a priori information about whether a context is likely for a given constituent based on whether the categories are combinable. Biasing our model towards both simple categories and connecting contexts encourages learning structures with simpler syntax and that have a better global “fit”.

Extends

acl_arc_intent_classification:train:1200

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: 4 To turn this likelihood into a certainty, one can add a test at the end of the algorithm, which adds a type-related property if none is present yet (cfXXX, Dale and Reiter 1995). 3 The degree of precision of the measurement (James et al. 1996, Section 1.5) determines which objects can be described by the GRE algorithm, since it determines which objects count as having the same size. Suppose the target is c4: Citation Sentence: 4 To turn this likelihood into a certainty , one can add a test at the end of the algorithm , which adds a type-related property if none is present yet ( cfXXX , Dale and Reiter 1995 ) . Context after the citation: VAGUE uses both of these devices. Since gradable properties are (for now at least) assumed to be dispreferred, the first property that makes it into L is ‘mouse,’ which removes p5 from the context set. (Result: C = {c1,...,c4}.) Now size is taken into account, and size(x) = 14 cm singles out c4.

Background

acl_arc_intent_classification:train:1201

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: For descriptions of SMT systems see for example (Germann et al., 2001; Och et al., 1999; Tillmann and Ney, 2002; Vogel et al., 2000; Wang and Waibel, 1997). In the work presented here, we restrict ourselves to transforming only one language of the two: the source, which has the less inflected morphology. If necessary, the inverse of these transformations will be applied to the generated output string. Citation Sentence: For descriptions of SMT systems see for example ( Germann et al. , 2001 ; Och et al. , 1999 ; Tillmann and Ney , 2002 ; Vogel et al. , 2000 ; Wang and Waibel , 1997 ) . Context after the citation:

Background

acl_arc_intent_classification:train:1202

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Such tools make it easy to run most current approaches to statistical markup, chunking, normalization, segmentation, alignment, and noisy-channel decoding,' including classic models for speech recognition (Pereira and Riley, 1997) and machine translation (Knight and Al-Onaizan, 1998). The availability of toolkits for this weighted case (Mohri et al., 1998; van Noord and Gerdemann, 2001) promises to unify much of statistical NLP. An artificial example will appear in §2. Citation Sentence: Such tools make it easy to run most current approaches to statistical markup , chunking , normalization , segmentation , alignment , and noisy-channel decoding , ' including classic models for speech recognition ( Pereira and Riley , 1997 ) and machine translation ( Knight and Al-Onaizan , 1998 ) . Context after the citation: Moreover, once the models are expressed in the finitestate framework, it is easy to use operators to tweak them, to apply them to speech lattices or other sets, and to combine them with linguistic resources. Unfortunately, there is a stumbling block: Where do the weights come from? After all, statistical models require supervised or unsupervised training. Currently, finite-state practitioners derive weights using exogenous training methods, then patch them onto transducer arcs.

Background

acl_arc_intent_classification:train:1203

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: It is analogous to the step in other translation model induction algorithms that sets all probabilities below a certain threshold to negligible values (Brown et al., 1990; Dagan et al., 1993; Chen, 1996). This step significantly reduces the computational burden of the algorithm. Discard all likelihood scores for word types deemed unlikely to be mutual translations, i.e. all L(u, v) < 1. Citation Sentence: It is analogous to the step in other translation model induction algorithms that sets all probabilities below a certain threshold to negligible values ( Brown et al. , 1990 ; Dagan et al. , 1993 ; Chen , 1996 ) . Context after the citation: To retain word type pairs that are at least twice as likely to be mutual translations than not, the threshold can be raised to 2. Conversely, the threshold can be lowered to buy more coverage at the cost of a larger model that will converge more slowly. 2. Sort all remaining likelihood estimates L(u, v) from highest to lowest.

CompareOrContrast

acl_arc_intent_classification:train:1204

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: The ConTroll grammar development system as described in (Gotz and Meurers, 1997b) implements the above mentioned techniques for compiling an HPSG theory into typed feature grammars. (Graz and Meurers, 1997b) describe a method for compiling implicational constraints into typed feature grammars and interleaving them with relational constraints.4 Because of space limitations we have to refrain from an example. which are used to restrict lexical entries. Citation Sentence: The ConTroll grammar development system as described in ( Gotz and Meurers , 1997b ) implements the above mentioned techniques for compiling an HPSG theory into typed feature grammars . Context after the citation:

Background

acl_arc_intent_classification:train:1205

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: After calculating the raw score of each sentence, we use a modified version of the Adaptive Greedy Algorithm by Filatova and Hatzivassiloglou (2004) to penalize redundant sentences in cohesive clusters. Removing redundant sentences. In order to ensure the relevance of the generated replies, we have placed tight restrictions on prediction probability and cluster cohesion (Table 3), which cause the Sent-Pred method to often return partial responses. Citation Sentence: After calculating the raw score of each sentence , we use a modified version of the Adaptive Greedy Algorithm by Filatova and Hatzivassiloglou ( 2004 ) to penalize redundant sentences in cohesive clusters . Context after the citation: This is done by decrementing the score of a sentence that belongs to an SC for which there is a higher or equal scoring sentence (if there are several highest-scoring sentences, we retain one sentence as a reference sentence—i.e., its score is not decremented). Specifically, given a sentence sk in cluster SCl which contains a sentence with a higher or equal score, the contribution of SCl to Score(sk) (= Pr(SCl) × Pr(sk|SCl)) is subtracted from Score(sk). After applying these penalties, we retain only the sentences whose adjusted score is greater than zero (for a highly cohesive cluster, typically only one sentence remains). 9 For each feature in the input (i.e., lemmatized words), the centroid of the cluster contains a frequency-based estimate of the probability that an item with this feature value appears in this cluster.

Uses

acl_arc_intent_classification:train:1206

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: If each word's translation is treated as a sense tag (Resnik and Yarowsky 1997), then &quot;translational&quot; collocations have the unique property that the collocate and the word sense are one and the same! in bitext space is another kind of collocation. The ratio links(u, v) I cooc (u, v), for several values of cooc(u, v). Citation Sentence: If each word 's translation is treated as a sense tag ( Resnik and Yarowsky 1997 ) , then `` translational '' collocations have the unique property that the collocate and the word sense are one and the same ! Context after the citation: Method B exploits this property under the hypothesis that &quot;one sense per collocation&quot; holds for translational collocations. This hypothesis implies that if u and v are possible mutual translations, and a token u co-occurs with a token v in the bitext, then with very high probability the pair (u, v) was generated from the same concept and should be linked. To test this hypothesis, I ran one iteration of Method A on 300,000 aligned sentence pairs from the Canadian Hansards bitext. I then plotted the

Uses

acl_arc_intent_classification:train:1207

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: The values of a vector correspond to the presence or absence of each (lemmatized) corpus word in the document in question (after removing stop-words and words with very low frequency).4 The predictive model is a Decision Graph (Oliver 1993), which, like Snob, is based on the MML principle. The input to Snob is a set of binary vectors, one vector per response document. We chose this program because the number of clusters does not have to be specified in advance, and it returns a probabilistic interpretation for its clusters (this interpretation is used by the Sent-Pred method, Section 3.2.2). Citation Sentence: The values of a vector correspond to the presence or absence of each ( lemmatized ) corpus word in the document in question ( after removing stop-words and words with very low frequency ) .4 The predictive model is a Decision Graph ( Oliver 1993 ) , which , like Snob , is based on the MML principle . Context after the citation: The Decision Graph is trained on unigram and bigram lemmas in the request as input features,5 and the identifier of the response cluster that contains the actual response for the request as the target feature. The model predicts which response cluster is most suitable for a given request, and returns the probability that this prediction is correct. This probability is our indicator of whether the Doc-Pred method can address a new request. As for the Doc-Ret method, an applicability threshold for this parameter is currently determined empirically (Table 3).

Uses

acl_arc_intent_classification:train:1208

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Therefore, in order to be able to incorporate long-range dependencies in our models, we chose to adopt a re-ranking approach (Collins 2000), which selects from likely assignments generated by a model which makes stronger independence assumptions. Training a model which has such a huge number of classes is infeasible if the model does not factorize due to strong independence assumptions. For argument labeling, the number of possible assignments is ≈ 20m, if m is the number of arguments of a verb (typically between 2 and 5), and 20 is the approximate number of possible labels if considering both core and modifying arguments. Citation Sentence: Therefore , in order to be able to incorporate long-range dependencies in our models , we chose to adopt a re-ranking approach ( Collins 2000 ) , which selects from likely assignments generated by a model which makes stronger independence assumptions . Context after the citation: We utilize the top n assignments of our local semantic role labeling model PSRL to generate likely assignments. As can be seen from Figure 8(a), for relatively small values of n, our re-ranking approach does not present a serious bottleneck to performance. We used a value of n = 10 for training.

Uses

acl_arc_intent_classification:train:1209

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Ratinov and Roth (2009) present detailed studies on the task of named entity recognition, which discusses and compares different methods on multiple aspects including chunk representation, inference method, utility of non-local features, and integration of external knowledge. However, the phrases detected are not necessarily mentions that we need to discover. Cardie and Pierce (1998) propose to select certain rules based on a given corpus, to identify base noun phrases. Citation Sentence: Ratinov and Roth ( 2009 ) present detailed studies on the task of named entity recognition , which discusses and compares different methods on multiple aspects including chunk representation , inference method , utility of non-local features , and integration of external knowledge . Context after the citation: NER can be regarded as a sequential labeling problem, which can be modeled by several proposed models, e.g. Hidden Markov Model (Rabiner, 1989) or Conditional Random Fields (Sarawagi and Cohen, 2004). The typical BIO representation was introduced in Ramshaw and Marcus (1995); OC representations were introduced in Church (1988), while Finkel and Manning (2009) further study nested named entity recognition, which employs a tree structure as a representation of identifying named entities within other named entities. The most relevant study on mentions in the context of coreference was done in Recasens et al. (2013); this work studies distinguishing single mentions from coreferent mentions. Our joint framework provides similar insights, where the added mention decision variable partly reflects if the mention is singleton or not.

Background

acl_arc_intent_classification:train:121

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: However, it is possible to think about constraining linguistic or logical predicates by simulating physical experiences (cfXXX Woods 1987). We investigate here only the &quot;grounding&quot; in logical theories. It is precisely this &quot;grounding&quot; of logical predicates in other conceptual structures that we would like to capture. Citation Sentence: However , it is possible to think about constraining linguistic or logical predicates by simulating physical experiences ( cfXXX Woods 1987 ) . Context after the citation: We assume here that a translation of the surface forms of sentences into a logical formalism is possible. Its details are not important for our aim of giving a semantic interpretation of paragraphs; the main theses of our theory do not depend on a logical notation. So we will use a very simple formalism, like the one above, resembling the standard first order language. But, obviously, there are other possibilities—for instance, the discourse representation structures (DRS's) of Kamp (1981), which have been used to translate a subset of English into logical formulas, to model text (identified with a list of sentences), to analyze a fragment of English, and to deal with anaphora.

Background

acl_arc_intent_classification:train:1210

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: One, the VOYAGER domain (Zue et al. 1990), answers questions about places of interest in an urban area, in our case, the vicinity of MIT and Harvard University. We currently have two application domains that can carry on a spoken dialog with a user. The perplexity (average number of words that can follow a given word) decreased from 70 to 28 to 8 when the grammar changed from wordpair (derived from the same grammar) to parser without probabilities to parser with probabilities. Citation Sentence: One , the VOYAGER domain ( Zue et al. 1990 ) , answers questions about places of interest in an urban area , in our case , the vicinity of MIT and Harvard University . Context after the citation: The second one, ATIS (Seneff et al. 1991), is a system for accessing data in the Official Airline Guide and booking flights. Work continues on improving all aspects of these domains. Our current research is directed at a number of different remaining issues.

Uses

acl_arc_intent_classification:train:1211

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Our task is closer to the work of Teufel and Moens (2000), who looked at the problem of intellectual attribution in scientific texts. Although this study falls under the general topic of discourse modeling, our work differs from previous attempts to characterize text in terms of domainindependent rhetorical elements (McKeown, 1985; Marcu and Echihabi, 2002). Nevertheless, their work bolsters our claims regarding the usefulness of generative models in extrinsic tasks, which we do not describe here. Citation Sentence: Our task is closer to the work of Teufel and Moens ( 2000 ) , who looked at the problem of intellectual attribution in scientific texts . Context after the citation:

CompareOrContrast

acl_arc_intent_classification:train:1212

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: In the seminal work by Rubenstein and Goodenough (1965), similarity judgments were obtained from 51 test subjects on 65 noun pairs written on paper cards. Citation Sentence: In the seminal work by Rubenstein and Goodenough ( 1965 ) , similarity judgments were obtained from 51 test subjects on 65 noun pairs written on paper cards . Context after the citation: Test subjects were instructed to order the cards according to the “similarity of meaning” and then assign a continuous similarity value (0.0 4.0) to each card. Miller and Charles (1991) replicated the experiment with 38 test subjects judging on a subset of 30 pairs taken from the original 65 pairs. This experiment was again replicated by Resnik (1995) with 10 subjects. Table 1 summarizes previous experiments.

Background

acl_arc_intent_classification:train:1213

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: (Och and Ney, 2002; Blunsom et al., 2008) used maximum likelihood estimation to learn weights for MT. (Och, 2003; Moore and Quirk, 2008; Zhao and Chen, 2009; Galley and Quirk, 2011) employed an evaluation metric as a loss function and directly optimized it. Several works have proposed discriminative techniques to train log-linear model for SMT. Citation Sentence: ( Och and Ney , 2002 ; Blunsom et al. , 2008 ) used maximum likelihood estimation to learn weights for MT. ( Och , 2003 ; Moore and Quirk , 2008 ; Zhao and Chen , 2009 ; Galley and Quirk , 2011 ) employed an evaluation metric as a loss function and directly optimized it . Context after the citation: (Watanabe et al., 2007; Chiang et al., 2008; Hopkins and May, 2011) proposed other optimization objectives by introducing a margin-based and ranking-based indirect loss functions. All the methods mentioned above train a single weight for the whole development set, whereas our local training method learns a weight for each sentence. Further, our translation framework integrates the training and testing into one unit, instead of treating them separately. One of the advantages is that it can adapt the weights for each of the test sentences.

CompareOrContrast

acl_arc_intent_classification:train:1214

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Jackendoff (1983, p. 14) writes &quot;it would be perverse not to take as a working assumption that language is a relatively efficient and accurate encoding of the information it conveys.&quot; Jackendoff's (1983) formalism is richer and resembles more closely an English grammar. notation of Montague (1970) is more sophisticated, and may be considered another possibility. Citation Sentence: Jackendoff ( 1983 , p. 14 ) writes `` it would be perverse not to take as a working assumption that language is a relatively efficient and accurate encoding of the information it conveys . '' Context after the citation: Therefore a formalism of the kind he advocates would probably be most suitable for an implementation of our semantics. It will also be a model for our simplified logical notation (cfXXX Section 5). We can envision a system that uses data structures produced by a computational grammar to obtain the logical form of sentences.

CompareOrContrast

acl_arc_intent_classification:train:1215

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: See also (Colmerauer, 1982; Naish, 1986). Whether or not a goal is sufficiently instantiated is determined on the basis of so-called delay patterns.13 These are specifications provided by the user that 12Coroutining appears under many different guises, like for example, suspension, residuation, (goal) freezing, and blocking. Finally, the used top-down interpreter implements a powerful coroutining mechanism:12 At run time the processing of a goal is postponed in case it is insufficiently instantiated. Citation Sentence: See also ( Colmerauer , 1982 ; Naish , 1986 ) . Context after the citation: &quot;In the literature delay patterns are sometimes also referred to as wait declarations or block statements. sk. non-parse type goals Proceedings of EACL '99 indicate which restricting information has to be available before a goal is processed.

Background

acl_arc_intent_classification:train:1216

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Michiels (1982) and Akkerman et al. (1985) provide a more detailed analysis of the information encoded by the LDOCE grammar codes and discuss their efficacy as a system of linguistic description. On the other hand, both believe and promise are assigned V3 which means they take a NP object and infinitival complement, yet there is a similar semantic distinction to be made between the two verbs; so the criteria for the assignment of the V code seem to be purely syntactic. The criteria for assignment of capital letters to verbs is not made explicit, but is influenced by the syntactic and semantic relations which hold between the verb and its arguments; for example, IS, L5 and T5 can all be assigned to verbs which take a NP subject and a sentential complement, but L5 will only be assigned if there is a fairly close semantic link between the two arguments and T5 will be used in preference to IS if the verb is felt to be semantically two place rather than one place, such as know versus appear. Citation Sentence: Michiels ( 1982 ) and Akkerman et al. ( 1985 ) provide a more detailed analysis of the information encoded by the LDOCE grammar codes and discuss their efficacy as a system of linguistic description . Context after the citation: Ingria (1984) comprehensively compares different approaches to complementation within grammatical theory providing a touchstone against which the LDOCE scheme can be evaluated. Most automated parsing systems employ grammars which carefully distinguish syntactic and semantic information, therefore, if the information provided by the Longman grammar code system is to be of use, we need to be able to separate out this information and map it into a representation scheme compatible with the type of lexicon used by such parsing systems. The program which transforms the LDOCE grammar codes into lexical entries utilisable by a parser takes as input the decompacted codes and produces a relatively theory neutral representation of the lexical entry for a particular word, in the sense that this representation could be further transformed into a format suitable for most current parsing systems. For example, if the input were the third sense of believe, as in Figure 4, the program would generate the (partial) entry shown in

Background

acl_arc_intent_classification:train:1217

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: We parsed the 3 GB AQUAINT corpus (Voorhees, 2002) using Minipar (Lin, 1998b), and collected verb-object and verb-subject frequencies, building an empirical MI model from this data. Citation Sentence: We parsed the 3 GB AQUAINT corpus ( Voorhees , 2002 ) using Minipar ( Lin , 1998b ) , and collected verb-object and verb-subject frequencies , building an empirical MI model from this data . Context after the citation: Verbs and nouns were converted to their (possibly multi-token) root, and string case was preserved. Passive subjects (the car was bought) were converted to objects (bought car). We set the MI-threshold, T, to be 0, and the negative-to-positive ratio, K, to be 2. Numerous previous pseudodisambiguation evaluations only include arguments that occur between 30 and 3000 times (Erk, 2007; Keller and Lapata, 2003; Rooth et al., 1999).

Uses

acl_arc_intent_classification:train:1218

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: More specifically, we use LIBSVM (Chang and Lin, 2001) with a quadratic kernel K(xZ, xj) = (-yxT xj +r)2 and the built-in one-versus-all strategy for multi-class classification. We use support vector machines3 to predict the next parser action from a feature vector representing the history. Citation Sentence: More specifically , we use LIBSVM ( Chang and Lin , 2001 ) with a quadratic kernel K ( xZ , xj ) = ( - yxT xj + r ) 2 and the built-in one-versus-all strategy for multi-class classification . Context after the citation: Symbolic features are 2The fields PHEAD and PDEPREL have not been used at all, since we rely on pseudo-projective parsing for the treatment of non-projective structures. 3We also ran preliminary experiments with memory-based learning but found that this gave consistently lower accuracy. converted to numerical features using the standard technique of binarization, and we split values of the FEATS field into its atomic components.4 For some languages, we divide the training data into smaller sets, based on some feature s (normally the CPOS or POS of the next input token), which may reduce training times without a significant loss in accuracy (Yamada and Matsumoto, 2003).

Uses

acl_arc_intent_classification:train:1219

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: mers (Lovins, 1968; Porter, 1980) demonstrably improve retrieval performance. For English, known for its limited number of inflection patterns, lexicon-free general-purpose stem1‘ ’ denotes the string concatenation operator. The efforts required for performing morphological analysis vary from language to language. Citation Sentence: mers ( Lovins , 1968 ; Porter , 1980 ) demonstrably improve retrieval performance . Context after the citation: This has been reported for other languages, too, dependent on the generality of the chosen approach (J¨appinen and Niemist¨o, 1988; Choueka, 1990; Popovic and Willett, 1992; Ekmekc¸ioglu et al., 1995; Hedlund et al., 2001; Pirkola, 2001). When it comes to a broader scope of morphological analysis, including derivation and composition, even for the English language only restricted, domain-specific algorithms exist. This is particularly true for the medical domain. From an IR view, a lot of specialized research has already been carried out for medical applications, with emphasis on the lexico-semantic aspects of dederivation and decomposition (Pacak et al., 1980; Norton and Pacak, 1983; Wolff, 1984; Wingert, 1985; Dujols et al., 1991; Baud et al., 1998).

Background

acl_arc_intent_classification:train:122

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: It is wasteful to compute ti as suggested earlier, by minimizing (cxxi)of o(yixE), since then the real work is done by an c-closure step (Mohri, 2002) that implements the all-pairs version of algebraic path, whereas all we need is the single-source version. Then ti is the total semiring weight w0n of paths in Ti from initial state 0 to final state n (assumed WLOG to be unique and unweighted). Let Ti = xiofoyi. Citation Sentence: It is wasteful to compute ti as suggested earlier , by minimizing ( cxxi ) of o ( yixE ) , since then the real work is done by an c-closure step ( Mohri , 2002 ) that implements the all-pairs version of algebraic path , whereas all we need is the single-source version . Context after the citation: If n and m are the number of states and edges,19 then both problems are O(n3) in the worst case, but the single-source version can be solved in essentially O(m) time for acyclic graphs and other reducible flow graphs (Tar an, 1981b). For a general graph Ti, Tar an (1981b) shows how to partition into “hard” subgraphs that localize the cyclicity or irreducibility, then run the O(n3) algorithm on each subgraph (thereby reducing n to as little as 1), and recombine the results. The overhead of partitioning and recombining is essentially only O(m). • For speeding up the O(n3) problem on subgraphs, one can use an approximate relaxation technique

Background

acl_arc_intent_classification:train:1220

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: positional features that have been employed by highwe can see, the baseline achieves an F-measure of performing resolvers such as Ng and Cardie (2002) 57.0 and a resolution accuracy of 48.4. Each instance is represented by 33 lexical, grammatical, semantic, and Following previous work (e.g., Soon et al. (2001) and Ponzetto and Strube (2006)), we generate training instances as follows: a positive instance is created for each anaphoric NP, NPj, and its closest antecedent, NPi; and a negative instance is created for NPj paired with each of the intervening NPs, NPi+1, NPi+2, ..., NPj_1. Citation Sentence: positional features that have been employed by highwe can see , the baseline achieves an F-measure of performing resolvers such as Ng and Cardie ( 2002 ) 57.0 and a resolution accuracy of 48.4 . Context after the citation: and Yang et al. (2003), as described below. To get a better sense of how strong our baseline Lexical features. Nine features allow different is, we re-implement the Soon et al. (2001) corefertypes of string matching operations to be performed ence resolver. This simply amounts to replacing the on the given pair of NPs, NP,, and NPy10, including 33 features in the baseline resolver with the 12 fea(1) exact string match for pronouns, proper nouns, tures employed by Soon et al.’s system.

CompareOrContrast

acl_arc_intent_classification:train:1221

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: Such a component would serve as the first stage of a clinical question answering system (Demner-Fushman and Lin, 2005) or summarization system (McKeown et al., 2003). Thus, our exploratory experiments in applying content models trained with structured RCTs on unstructured RCTs is a closer approximation of an extrinsically-valid measure of performance. The true utility of content models is to structure abstracts that have no structure to begin with. Citation Sentence: Such a component would serve as the first stage of a clinical question answering system ( Demner-Fushman and Lin , 2005 ) or summarization system ( McKeown et al. , 2003 ) . Context after the citation: We chose to focus on randomized controlled trials because they represent the standard benchmark by which all other clinical studies are measured. Table 3(b) shows the effectiveness of our trained content models on abstracts that had no explicit structure to begin with. We can see that although classification accuracy is lower than that from our cross-validation experiments, performance is quite respectable. Thus, our hypothesis that unstructured abstracts are not qualitatively different from structured abstracts appears to be mostly valid.

FutureWork

acl_arc_intent_classification:train:1222

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Briscoe and Carroll (1997) predefine 163 verbal subcategorization frames, obtained by manually merging the classes exemplified in the COMLEX (MacLeod, Grishman, and Meyers 1994) and ANLT (Boguraev et al. 1987) dictionaries and adding around 30 frames found by manual inspection. Applying his technique to approximately four million words of New York Times newswire, Manning acquired 4,900 verb-subcategorization frame pairs for 3,104 verbs, an average of 1.6 frames per verb. The extracted frames are noisy as a result of parser errors and so are filtered using the binomial hypothesis theory (BHT), following Brent (1993). Citation Sentence: Briscoe and Carroll ( 1997 ) predefine 163 verbal subcategorization frames , obtained by manually merging the classes exemplified in the COMLEX ( MacLeod , Grishman , and Meyers 1994 ) and ANLT ( Boguraev et al. 1987 ) dictionaries and adding around 30 frames found by manual inspection . Context after the citation: The frames incorporate control information and details of specific prepositions. Briscoe and Carroll (1997) refine the BHT with a priori information about the probabilities of subcategorization frame membership and use it to filter the induced frames. Recent work by Korhonen (2002) on the filtering phase of this approach uses linguistic verb classes (based on Levin [1993]) for obtaining more accurate back-off estimates for hypothesis selection. Carroll and Rooth (1998) use a handwritten head-lexicalized, context-free grammar and a text corpus to compute the probability of particular subcategorization patterns.

Background

acl_arc_intent_classification:train:1223

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: The idea resurfaced forcefully at several points in the more recent history of linguistic research (Tesni`ere, 1959; Gruber, 1965; Fillmore, 1968). He was a grammarian who analysed Sanskrit (Misra, 1966). The first chronicled endeavour to connect text elements and organise connections between them goes back to the 51h century B.C. and the work of Paninil. Citation Sentence: The idea resurfaced forcefully at several points in the more recent history of linguistic research ( Tesni`ere , 1959 ; Gruber , 1965 ; Fillmore , 1968 ) . Context after the citation: Now it has the attention of many researchers in natural language processing, as shown by recent research in semantic parsing and semantic 'The sources date his work variously between the 5th and 7th century. Graph-like structures are a natural way of organising one’s impressions of a text seen from the perspective of connections between its simpler constituents of varying granularity, from sections through paragraphs, sentences, clauses, phrases, words to morphemes. In this work we pursue a well-known and often tacitly assumed line of thinking: connections at the syntactic level reflect connections at the semantic level (in other words, syntax carries meaning).

Background

acl_arc_intent_classification:train:1224

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: It is therefore no surprise that early attempts at response automation were knowledge-driven (Barr and Tessler 1995; Watson 1997; Delic and Lahaix 1998). circumstances can make each inquiry unique, and hence care must be taken to compose a response that does not confuse, irritate, or mislead the customer. 1 http://customercare.telephonyonline.com/ar/telecom next generation customer. Citation Sentence: It is therefore no surprise that early attempts at response automation were knowledge-driven ( Barr and Tessler 1995 ; Watson 1997 ; Delic and Lahaix 1998 ) . Context after the citation: These systems were carefully designed to produce relevant and correct responses, but required significant human input and maintenance (Delic and Lahaix 1998). In recent times, such knowledge-intensive approaches to content delivery have been largely superseded by data-intensive, statistical approaches. An outcome of the recent proliferation of statistical approaches, in particular in recommender systems and search engines, is that people have become accustomed to responses that are not precisely tailored to their queries. This indicates that help-desk customers may have also become more tolerant of inaccurate or incomplete automatically generated replies, provided these replies are still relevant to their problem, and so long as the customers can follow up with a request for human-generated responses if necessary.

Background

acl_arc_intent_classification:train:1225

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: For example, the suite of LT tools (Mikheev et al., 1999; Grover et al., 2000) perform tokenization, tagging and chunking on XML marked-up text directly. A number of stand-alone tools have also been developed. This allows components to be highly configurable and simplifies the addition of new components to the system. Citation Sentence: For example , the suite of LT tools ( Mikheev et al. , 1999 ; Grover et al. , 2000 ) perform tokenization , tagging and chunking on XML marked-up text directly . Context after the citation: These tools also store their configuration state, e.g. the transduction rules used in LT CHUNK, in XML configuration files. This gives a greater flexibility but the tradeoff is that these tools can run very slowly. Other tools have been designed around particular techniques, such as finite state machines (Karttunen et al., 1997; Mohri et al., 1998). However, the source code for these tools is not freely available, so they cannot be extended.

Background

acl_arc_intent_classification:train:1226

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: It is only recently that the web name ambiguity has been approached as a separate problem and defined as an NLP task Web People Search on its own (Artiles et al., 2005; Artiles et al., 2007). Most of early research work on person name ambiguity focuses on the CDC problem or uses methods found in the WSD literature. The disambiguation of person names in Web results is usually compared to two other Natural Language Processing tasks: Word Sense Disambiguation (WSD) (Agirre and Edmonds, 2006) and Cross-document Coreference (CDC) (Bagga and Baldwin, 1998). Citation Sentence: It is only recently that the web name ambiguity has been approached as a separate problem and defined as an NLP task Web People Search on its own ( Artiles et al. , 2005 ; Artiles et al. , 2007 ) . Context after the citation: Therefore, it is useful to point out some crucial differences between WSD, CRC and WePS: • WSD typically concentrates in the disambiguation of common words (nouns, verbs, adjectives) for which a relatively small number of senses exist, compared to the hundreds or thousands of people that can share the same name. • WSD can rely on dictionaries to define the number of possible senses for a word. In the case of name ambiguity no such dictionary is available, even though in theory there is an exact number of people that can be accounted as sharing the same name.

Uses

acl_arc_intent_classification:train:1227

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: To retrieve translation examples for a test sentence, (Watanabe and Sumita, 2003) defined a metric based on the combination of edit distance and TF-IDF (Manning and Sch¨utze, 1999) as follows: The metric we consider here is derived from an example-based machine translation. We assume that the metric satisfy the property: more similar the test sentence and translation examples are, the better translation result one obtains when decoding the test sentence with the weight trained on the translation examples. Citation Sentence: To retrieve translation examples for a test sentence , ( Watanabe and Sumita , 2003 ) defined a metric based on the combination of edit distance and TF-IDF ( Manning and Sch ¨ utze , 1999 ) as follows : Context after the citation: where 0(0 < 0 < 1) is an interpolation weight, fi(i = 1, 2) is a word sequence and can be also considered as a document. In this paper, we extract similar examples from training data. Like examplebased translation in which similar source sentences have similar translations, we assume that the optimal translation weights of the similar source sentences are closer. 4 Incremental Training Based on Ultraconservative Update

Uses

acl_arc_intent_classification:train:1228

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: By using the EM algorithm (Dempster et al., 1977), they can guarantee convergence towards the globally optimum parameter set. One advantage that Brown et al.'s Model 1 has over our word-to-word model is that their objective function has no local maxima. It is not clear how the precision/recall tradeoff can be controlled in the IBM models. Citation Sentence: By using the EM algorithm ( Dempster et al. , 1977 ) , they can guarantee convergence towards the globally optimum parameter set . Context after the citation: In contrast, the dynamic nature of the competitive linking algorithm changes the Pr(datalmodel) in a non-monotonic fashion. We have adopted the simple heuristic that the model &quot;has converged&quot; when this probability stops increasing.

Background

acl_arc_intent_classification:train:1229

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: Cases like this would be covered if the decision-theoretic property of Pareto optimality (e.g., Feldman 1980) was used as the sole criterion: Formally, an object r E C has a Pareto-optimal combination of Values V iff there is no other x E C such that The NP the tall fat giraffe, for example, can safely refer to an element b in a situation like the one below, where b is the only element that exceeds all distractors with respect to some dimension (a different one for a than for c, as it happens) while not being exceeded by any distractors in any dimension: Let us focus on references to an individual referent r, starting with a description that contains more than one gradable adjective. Citation Sentence: Cases like this would be covered if the decision-theoretic property of Pareto optimality ( e.g. , Feldman 1980 ) was used as the sole criterion : Formally , an object r E C has a Pareto-optimal combination of Values V iff there is no other x E C such that Context after the citation: 1. ] Vi E V : Vi(x) > Vi(r) and 2. -]Vj E V : Vj(x) < Vj(r) In our example, b is the only object that has a Pareto-optimal combination of Values, predicting correctly that b can be called the tall fat giraffe.

Background

acl_arc_intent_classification:train:123

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: • use of low level knowledge from the speech recognition phase, • use of high level knowledge about the domain in particular and the dialogue task in general, • a &quot;continue&quot; facility and an &quot;auto-loop&quot; facility as described by Biermann and Krishnaswamy (1976), • a &quot;conditioning&quot; facility as described by Fink et al. (1985), • implementation of new types of paraphrasing, • checking a larger environment in the expectation acquisition algorithm when deciding if an incoming sentence is the same or similar to one already seen, and • examining inter-speaker dialogue patterns. These include the following: However, there are many possible extensions that could be examined in the future and added to the implementation if the investigation indicates that it would create a yet more usable system. Citation Sentence: • use of low level knowledge from the speech recognition phase , • use of high level knowledge about the domain in particular and the dialogue task in general , • a `` continue '' facility and an `` auto-loop '' facility as described by Biermann and Krishnaswamy ( 1976 ) , • a `` conditioning '' facility as described by Fink et al. ( 1985 ) , • implementation of new types of paraphrasing , • checking a larger environment in the expectation acquisition algorithm when deciding if an incoming sentence is the same or similar to one already seen , and • examining inter-speaker dialogue patterns . Context after the citation: All but two of these areas for expansion are aimed at moving the expectation system from one that finds patterns in a user's dialogues and acquires historical knowledge about them to one that can acquire true procedures. The first two areas for expansion have nothing to do with creating a true procedure acquisition module but would be highly desirable from the point of view of the speech recognition application. Features three and four would simply make the system easier to use and would require little theoretical investigation. The final three would require research efforts.

FutureWork

acl_arc_intent_classification:train:1230

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Previous work has developed various approaches for grounded semantics mainly for the reference resolution task, i.e., identifying visual objects in the environment given language descriptions (Dhande, 2003; Gorniak and Roy, 2004; Tenbrink and Moratz, 2003; Siebert and Schlangen, 2008; Liu et al., 2012). Grounded semantics provides a bridge to connect symbolic labels or words with lower level visual features (Harnad, 1990). Citation Sentence: Previous work has developed various approaches for grounded semantics mainly for the reference resolution task , i.e. , identifying visual objects in the environment given language descriptions ( Dhande , 2003 ; Gorniak and Roy , 2004 ; Tenbrink and Moratz , 2003 ; Siebert and Schlangen , 2008 ; Liu et al. , 2012 ) . Context after the citation: For the referring expression generation task here, we also need a lexicon with grounded semantics. In our lexicon, the semantics of each category of words is defined by a set of semantic grounding functions that are parameterized on visual features. For example, for the color category it is defined as a multivariate Gaussian distribution based on the RGB distribution. Specific words such as green, red, or blue have different means and co-variances as the following:

Extends

acl_arc_intent_classification:train:1231

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: In most recent research, NEs (person, location and organisations) are extracted from the text and used as a source of evidence to calculate the similarity between documents -see for instance (Blume, 2005; Chen and Martin, 2007; Popescu and Magnini, 2007; Kalashnikov et al., 2007). Ravin (1999) introduced a rule-based approach that tackles both variation and ambiguity analysing the structure of names. The most used feature for the Web People Search task, however, are NEs. Citation Sentence: In most recent research , NEs ( person , location and organisations ) are extracted from the text and used as a source of evidence to calculate the similarity between documents - see for instance ( Blume , 2005 ; Chen and Martin , 2007 ; Popescu and Magnini , 2007 ; Kalashnikov et al. , 2007 ) . Context after the citation: For instance, Blume (2005) uses NEs coocurring with the ambiguous mentions of a name as a key feature for the disambiguation process. Saggion (2008) compared the performace of NEs versus BoW features. In his experiments a only a representation based on Organisation NEs outperformed the word based approach. Furthermore, this result is highly dependent on the choice of metric weighting (NEs achieve high precision at the cost of a low recall and viceversa for BoW).

Background

acl_arc_intent_classification:train:1232

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: To provide the required configurability in the static version of the code we will use policy templates (Alexandrescu, 2001), and for the dynamic version we will use configuration classes. However, because templates are a static facility we will also provide dynamic versions (using inheritance), which will be slower but accessible from scripting languages and user interfaces. Templates will be used heavily to provide generality without significantly impacting on efficiency. Citation Sentence: To provide the required configurability in the static version of the code we will use policy templates ( Alexandrescu , 2001 ) , and for the dynamic version we will use configuration classes . Context after the citation: A key aspect of increasing the efficiency of the system will be using a common text and annotation representation throughout the infrastructure. This means that we do not need to save data to disk, and load it back into memory between each step in the process, which will provide a significant performance increase. Further, we can use techniques for making string matching and other text processing very fast such as making only one copy of each lexical item or annotation in memory. We can also load a lexicon into memory that is shared between all of the components, reducing the memory use.

Uses

acl_arc_intent_classification:train:1233

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: Lee et al. (2003) demonstrates a technique for segmenting Arabic text and uses it as a morphological processing step in machine translation. Citation Sentence: Lee et al. ( 2003 ) demonstrates a technique for segmenting Arabic text and uses it as a morphological processing step in machine translation . Context after the citation: A trigram language model was used to score and select among hypothesized segmentations determined by a set of prefix and suffix expansion rules. In our latest implementation of this algorithm, we have recast this segmentation strategy as the composition of three distinct finite state machines. The first machine, illustrated in Figure 1 encodes the prefix and suffix expansion rules, producing a lattice of possible segmentations. The second machine is a dictionary that accepts characters and produces identifiers corresponding to dictionary entries.

Uses

acl_arc_intent_classification:train:1234

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: In informal experiments described elsewhere (Melamed 1995), I found that the G2 statistic suggested by Dunning (1993) slightly outperforms 02. For example, Gale and Church (1991, 154) suggest that &quot;02, a x2-like statistic, seems to be a particularly good choice because it makes good use of the off-diagonal cells&quot; in the contingency table. The statistical interdependence between two word types can be estimated more robustly by considering the whole table. Citation Sentence: In informal experiments described elsewhere ( Melamed 1995 ) , I found that the G2 statistic suggested by Dunning ( 1993 ) slightly outperforms 02 . Context after the citation: Let the cells of the contingency table be named as follows: where B(kin,p) = () pk(1 p)n-k are binomial probabilities. The statistic uses maximum likelihood estimates for the probability parameters: p1 = bf P2 — c±cd' P = a±ab±±cc-Fd' G2 is easy to compute because the binomial coefficients in the numerator and in the denominator cancel each other out. All my methods initialize the parameters score(u,v) to G2(u, v), except that any pairing with NULL is initialized to an infinitesimal value.

Extends

acl_arc_intent_classification:train:1235

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: • language learning (Green 1979; Mori and Moeser 1983; Morgan, Meier, and Newport 1989) • monolingual grammar induction (Juola 1998) • grammar optimization (Juola 1994) • insights into universal grammar (Juola 1998) • machine translation (Juola 1994, 1997; Veale and Way 1997; Gough, Way, and Hearne 2002) The marker hypothesis has been used for a number of different language-related tasks, including The marker hypothesis is arguably universal in presuming that concepts and structures like these have similar morphological or structural marking in all languages. Citation Sentence: • language learning ( Green 1979 ; Mori and Moeser 1983 ; Morgan , Meier , and Newport 1989 ) • monolingual grammar induction ( Juola 1998 ) • grammar optimization ( Juola 1994 ) • insights into universal grammar ( Juola 1998 ) • machine translation ( Juola 1994 , 1997 ; Veale and Way 1997 ; Gough , Way , and Hearne 2002 ) Context after the citation: With respect to translation, a potential problem in using the marker hypothesis is that some languages do not have marker words such as articles, for instance. Green’s (1979) work showed that artificial languages, both with and without specific marker words, may be learned more accurately and quickly if such psycholinguistic cues exist. The research of Mori and Moeser (1983) showed a similar effect due to case marking on pseudowords in such artificial languages, and Morgan, Meier, and Newport (1989) demonstrated that languages that do not permit pronouns as substitutes for phrases also provide evidence in favor of the marker hypothesis.

Background

acl_arc_intent_classification:train:1236

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: A recent study by Katz-Brown et al. (2011) also investigates the task of training parsers to improve MT reordering. Citation Sentence: A recent study by Katz-Brown et al. ( 2011 ) also investigates the task of training parsers to improve MT reordering . Context after the citation: In that work, a parser is used to first parse a set of manually reordered sentences to produce k-best lists. The parse with the best reordering score is then fixed and added back to the training set and a new parser is trained on resulting data. The method is called targeted self-training as it is similar in vein to self-training (McClosky et al., 2006), with the exception that the new parse data is targeted to produce accurate word reorderings. Our method differs as it does not statically fix a new parse, but dynamically updates the parameters and parse selection by incorporating the additional loss in the inner loop of online learning.

CompareOrContrast

acl_arc_intent_classification:train:1237

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Due to their remarkable ability to incorporate context structure information and long distance reordering into the translation process, tree-based translation models have shown promising progress in improving translation quality (Liu et al., 2006, 2009; Quirk et al., 2005; Galley et al., 2004, 2006; Marcu et al., 2006; Shen et al., 2008; Zhang et al., 2011b). In recent years, tree-based translation models1 are drawing more and more attention in the community of statistical machine translation (SMT). Citation Sentence: Due to their remarkable ability to incorporate context structure information and long distance reordering into the translation process , tree-based translation models have shown promising progress in improving translation quality ( Liu et al. , 2006 , 2009 ; Quirk et al. , 2005 ; Galley et al. , 2004 , 2006 ; Marcu et al. , 2006 ; Shen et al. , 2008 ; Zhang et al. , 2011b ) . Context after the citation: However, tree-based translation models always suffer from two major challenges: 1) They are usually built directly from parse trees, which are generated by supervised linguistic parsers. 1 A tree-based translation model is defined as a model using tree structures on one side or both sides. However, for many language pairs, it is difficult to acquire such corresponding linguistic parsers due to the lack of Tree-bank resources for training. 2) Parse trees are actually only used to model and explain the monolingual structure, rather than the bilingual mapping between language pairs.

Background

acl_arc_intent_classification:train:1238

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: 15 Hinrichs and Nakazawa (1996) show that the question of whether the application criterion of lexical rules should be a subsumption or a unification test is an important question deserving of more attention. 14 We use rather abstract lexical rules in the examples to be able to focus on the relevant aspects. 13 A more detailed presentation can be found in Minnen (in preparation). Citation Sentence: 15 Hinrichs and Nakazawa ( 1996 ) show that the question of whether the application criterion of lexical rules should be a subsumption or a unification test is an important question deserving of more attention . Context after the citation: We here assume unification as the application criterion, which formally corresponds to the conjunction of descriptions and their conversion to normal form (Glitz 1994). Computationally, a subsumption test could equally well be used in our compiler. The compiler setup. in Figure 6.

Background

acl_arc_intent_classification:train:1239

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: A formula for the test set perplexity (Lee 1989) is:13 The grammar could parse 100% of the training sentences and 84% of the test sentences. We built a subset grammar from the 791 parsed training sentences, and then used this grammar to test coverage and perplexity on the unseen test sentences. Citation Sentence: A formula for the test set perplexity ( Lee 1989 ) is :13 Context after the citation: where the wi are the sequence of all words in all sentences, N is the total number of words, including an &quot;end&quot; word after each sentence, and P(w, I w,_1,...wi) is the probability of the ith word given all preceding words.14 If all words are assumed equally likely, then P(w, I w,_1,...w1) can be determined by counting all the words that could follow each word in the sentence, along all workable partial theories. If the grammar contains probability estimates, then these can be used in place of the equally 13 The appendix includes an example for computing test set perplexity. 14 In the case of TINA, all words up to the current word within each sentence are relevant.

Background

acl_arc_intent_classification:train:124

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: Latent Dirichlet Allocation (Blei et al., 2003), or LDA, is an unsupervised Bayesian probabilistic model of text documents. Citation Sentence: Latent Dirichlet Allocation ( Blei et al. , 2003 ) , or LDA , is an unsupervised Bayesian probabilistic model of text documents . Context after the citation: It assumes that all documents are probabilistically generated from a shared set of K common topics, where each topic is a multinomial distribution over the vocabulary (notated as Q), and documents are modeled as mixtures of these shared topics (notated as 0). LDA assumes every document in the corpus is generated using the fol- lowing generative process: 1.

Background

acl_arc_intent_classification:train:1240

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: conclusion Context before the citation: Regarding future work, there are many research line that may be followed: i) Capturing more features by employing external knowledge such as ontological, lexical resource or WordNet-based features (Basili et al., 2005a; Basili et al., 2005b; Bloehdorn et al., 2006; Bloehdorn and Moschitti, 2007) or shallow semantic trees, (Giuglea and Moschitti, 2004; Giuglea and Moschitti, 2006; Moschitti and Bejan, 2004; Moschitti et al., 2007; Moschitti, 2008; Moschitti et al., 2008). Our novel composite kernels, which account for the two syntactic structures, are experimented with the appropriate convolution kernels and show significant improvement with respect to the state-ofthe-art in RE. For the design of automatic relation classifiers, we have investigated the impact of dependency structures to the RE task. Citation Sentence: Regarding future work , there are many research line that may be followed : i ) Capturing more features by employing external knowledge such as ontological , lexical resource or WordNet-based features ( Basili et al. , 2005a ; Basili et al. , 2005b ; Bloehdorn et al. , 2006 ; Bloehdorn and Moschitti , 2007 ) or shallow semantic trees , ( Giuglea and Moschitti , 2004 ; Giuglea and Moschitti , 2006 ; Moschitti and Bejan , 2004 ; Moschitti et al. , 2007 ; Moschitti , 2008 ; Moschitti et al. , 2008 ) . Context after the citation: ii) Design a new tree-based structures, which combines the information of both constituent and dependency parses. From dependency trees we can extract more precise but also more sparse relationships (which may cause overfit). From constituent trees, we can extract subtrees constituted by non-terminal symbols (grammar symbols), which provide a better generalization (with a risk of underfitting). iii) Design a new kernel which can integrate the advantages of the constituent and dependency tree.

FutureWork

acl_arc_intent_classification:train:1241

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Third, the paradigm of evidence-based medicine (Sackett et al. 2000) provides a task-based model of the clinical information-seeking process. The Semantic Network provides a consistent categorization of all concepts represented in the UMLS Metathesaurus. The 2004 version of the UMLS Metathesaurus (used in this work) contains information about over 1 million biomedical concepts and 5 million concept names from more than 100 controlled vocabularies. Citation Sentence: Third , the paradigm of evidence-based medicine ( Sackett et al. 2000 ) provides a task-based model of the clinical information-seeking process . Context after the citation: The PICO framework (Richardson et al. 1995) for capturing well-formulated clinical queries (described in Section 2) can serve as the basis of a knowledge representation that bridges the needs of clinicians and analytical capabilities of a system. The confluence of these many factors makes clinical question answering a very exciting area of research. Furthermore, the need to answer questions related to patient care at the point of service has been well studied and documented (Covell, Uman, and Manning 1985; Gorman, Ash, and Wykoff 1994; Ely et al. 1999, 2005). MEDLINE, the authoritative repository of abstracts from the medical and biomedical primary literature maintained by the National Library of Medicine, provides the clinically relevant sources for answering physicians’ questions, and is commonly used in that capacity (Cogdill and Moore 1997; De Groote and Dorsch 2003).

Background

acl_arc_intent_classification:train:1242

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Koehn and Hoang (2007) introduced factored SMT. There has been other work on solving inflection. The only work that we are aware of which deals with both issues is the work of de Gispert and Mari˜no (2008), which deals with verbal morphology and attached pronouns. Citation Sentence: Koehn and Hoang ( 2007 ) introduced factored SMT . Context after the citation: We use more complex context features. Fraser (2009) tried to solve the inflection prediction problem by simply building an SMT system for translating from stems to inflected forms. Bojar and Kos (2010) improved on this by marking prepositions with the case they mark (one of the most important markups in our system). Both efforts were ineffective on large data sets.

CompareOrContrast

acl_arc_intent_classification:train:1243

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Both systems are built around from the maximum-entropy technique (Berger et al., 1996). Both tasks are performed with a statistical framework: the mention detection system is similar to the one presented in (Florian et al., 2004) and the coreference resolution system is similar to the one described in (Luo et al., 2004). It is these orthographic variations and complex morphological structure that make Arabic language processing challenging (Xu et al., 2001; Xu et al., 2002). Citation Sentence: Both systems are built around from the maximum-entropy technique ( Berger et al. , 1996 ) . Context after the citation: We formulate the mention detection task as a sequence classification problem. While this approach is language independent, it must be modified to accomodate the particulars of the Arabic language. The Arabic words may be composed of zero or more prefixes, followed by a stem and zero or more suffixes. We begin with a segmentation of the written text before starting the classification.

Uses

acl_arc_intent_classification:train:1244

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: We chose the adjectives as follows: we first compiled a list of all the polysemous adjectives mentioned in the lexical semantics literature (Vendler, 1968; Pustejovsky, 1995). We chose nine adjectives according to a set of minimal criteria and paired each adjective with 10 nouns randomly selected from the BNC. 3.1.1 Materials and Design Citation Sentence: We chose the adjectives as follows : we first compiled a list of all the polysemous adjectives mentioned in the lexical semantics literature ( Vendler , 1968 ; Pustejovsky , 1995 ) . Context after the citation: From these we randomly sampled nine adjectives (difficult, easy, fast, good, hard, right, safe, slow, wrong). These adjectives had to be unambiguous with respect to their part-of-speech: each adjective was unambiguously tagged as “adjective” 98.6% of the time, measured as the number of different part-of-speech tags assigned to the word in the BNC. We identified adjective-noun pairs using Gsearch (Corley et al., 2000), a chart parser which detects syntactic patterns in a tagged corpus by exploiting a userspecified context free grammar and a syntactic query. Gsearch was run on a lemmatized version of the BNC so as to compile a comprehensive corpus count of all nouns occurring in a modifier-head relationship with each of the nine adjectives.

Uses

acl_arc_intent_classification:train:1245

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Most web-derived corpora have exploited raw text or HTML pages, so efforts have focussed on boilerplate removal and cleanup of these formats with tools like Hyppia-BTE, Tidy and Parcels3 (Baroni and Sharoff, 2005). A key aspect of our case study research will be to investigate extending corpus collection to new document types. We can evaluate annotation speed gains of our approach comparatively against the single server version by utilising processing power in computer labs at Lancaster University and the United States Naval Academy (USNA) and we will call for volunteers from the corpus community to be involved in the evaluation as well. Citation Sentence: Most web-derived corpora have exploited raw text or HTML pages , so efforts have focussed on boilerplate removal and cleanup of these formats with tools like Hyppia-BTE , Tidy and Parcels3 ( Baroni and Sharoff , 2005 ) . Context after the citation: Other document formats such as Adobe PDF and MS-Word have been neglected due to the extra conversion and clean-up problems they entail. By excluding PDF documents, web-derived corpora are less representative of certain genres such as academic writing. 2 http://setiathome.ssl.berkeley.edu/ 3 http://www.smi.ucd.ie/hyppia/, http://parcels.sourceforge.net and http://tidy.sourceforge.net.

Background

acl_arc_intent_classification:train:1246

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Undesirable consequences of this fact have been termed “label bias” (Lafferty et al., 2001). Unfortunately, the result may differ for equivalent FSTs that express the same weighted relation. • An easy approach is to normalize the options at each state to make the FST Markovian. Citation Sentence: Undesirable consequences of this fact have been termed `` label bias '' ( Lafferty et al. , 2001 ) . Context after the citation: Also, in the conditional case such per-state normalization is only correct if all states accept all input suffixes (since “dead ends” leak probability mass).8 • A better-founded approach is global normal- ization, which simply divides each f(x, y) by Ex,,y, f(x', y') (joint case) or by Ey, f(x, y') (conditional case). To implement the joint case, just divide stopping weights by the total weight of all paths (which §4 shows how to find), provided this is finite. In the conditional case, let g be a copy of f with the output labels removed, so that g(x) finds the desired divisor; determinize g if possible (but this fails for some weighted FSAs), replace all weights with their reciprocals, and compose the result with f.9 6P(w, x) defines the source model, and is often an “identity FST” that requires w = x, really just an FSA.

Background

acl_arc_intent_classification:train:1247

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: For the full parser, we use the one developed by Michael Collins (Collins, 1996; Collins, 1997) — one of the most accurate full parsers around. We perform our comparison using two state-ofthe-art parsers. Citation Sentence: For the full parser , we use the one developed by Michael Collins ( Collins , 1996 ; Collins , 1997 ) -- one of the most accurate full parsers around . Context after the citation: It represents a full parse tree as a set of basic phrases and a set of dependency relationships between them. Statistical learning techniques are used to compute the probabilities of these phrases and of candidate dependency relations occurring in that sentence. After that, it will choose the candidate parse tree with the highest probability as output. The experiments use the version that was trained (by Collins) on sections 02-21 of the Penn Treebank.

Uses

acl_arc_intent_classification:train:1248

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: Some researchers, however, including Goldberg and Elhadad (2010), train on predicted feature values instead. So far, we have only evaluated models trained on gold POS tag set and morphological feature values. Combined Gold and Predicted Features for Training Citation Sentence: Some researchers , however , including Goldberg and Elhadad ( 2010 ) , train on predicted feature values instead . Context after the citation: It makes sense that training on predicted features yields better scores for evaluation on predicted features, since the training better resembles the test. But we argue that it also makes sense that training on a combination of gold and predicted features (one copy of each) might do even better, because good predictions of feature values are reinforced (since they repeat the gold patterns), whereas noisy predicted feature values are still represented in training (in patterns that do not repeat the gold).21 To test our hypothesis, we start this section by comparing three variations: • Training on gold feature values (as has been the case so far) • Training on predicted feature values (as in Goldberg and Elhadad 2010) • Training on the novel combination of gold and predicted features (denoted below as g+p) 20 Recall that DET2 was only defined for MaltParser, and not for the Easy-First Parser.

CompareOrContrast

acl_arc_intent_classification:train:1249

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: This method follows a traditional Information Retrieval paradigm (Salton and McGill 1983), where a query is represented by the content terms it contains, and the system retrieves from the corpus a set of documents that best match this query. 3.1.1 Document Retrieval (Doc-Ret). As stated herein, we studied two document-based methods: Document Retrieval and Document Prediction. Citation Sentence: This method follows a traditional Information Retrieval paradigm ( Salton and McGill 1983 ) , where a query is represented by the content terms it contains , and the system retrieves from the corpus a set of documents that best match this query . Context after the citation: In our case, the query is a new request e-mail to be addressed by the system, and we have considered three views of the documents in the corpus: (1) previous response e-mails, (2) previous request e-mails, or (3) previous request– response pairs. The first alternative corresponds to the more traditional view of retrieval as applied in question-answering tasks, where the terms in the question are matched to those in the answer documents. We consider the second alternative in order to address situations such as the example in Figure 1(c), where a request might not match a particular response, but it may match another request, yielding the response to that request. The third alternative addresses situations where a new request matches part of another request and part of its response.

Uses

acl_arc_intent_classification:train:125

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Their computational significance arises from the issue of their storage in lexical resources like WordNet (Fellbaum, 1998) and raises the questions like, how to store morphologically complex words, in a lexical resource like WordNet keeping in mind the storage and access efficiency. Further, these linguistically important and interesting questions are also highly significant for computational linguistics (CL) and natural language processing (NLP) applications. A clear understanding of the structure and the processing mechanism of the mental lexicon will further our knowledge of how the human brain processes language. Citation Sentence: Their computational significance arises from the issue of their storage in lexical resources like WordNet ( Fellbaum , 1998 ) and raises the questions like , how to store morphologically complex words , in a lexical resource like WordNet keeping in mind the storage and access efficiency . Context after the citation: There is a rich literature on organization and lexical access of morphologically complex words where experiments have been conducted mainly for derivational suffixed words of English, Hebrew, Italian, French, Dutch, and few other languages (Marslen-Wilson et al., 2008; Frost et al., 1997; Grainger, et al., 1991; Drews and Zwitserlood, 1995). However, we do not know of any such investigations for Indian languages, which are morphologically richer than many of their Indo-European cousins. Moreover, Indian languages show some distinct phenomena like, compound and composite verbs for which no such investigations have been conducted yet.

Background

acl_arc_intent_classification:train:1250

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Fortunately, there exists a compact PCFG-reduction of DOP1 that generates the same trees with the same probabilities, as shown by Goodman (1996, 2002). A disadvantage of this model is that an extremely large number of subtrees (and derivations) must be taken into account. Thus DOP1 considers counts of subtrees of a wide range of sizes in computing the probability of a tree: everything from counts of single-level rules to counts of entire trees. Citation Sentence: Fortunately , there exists a compact PCFG-reduction of DOP1 that generates the same trees with the same probabilities , as shown by Goodman ( 1996 , 2002 ) . Context after the citation: Here we will only sketch this PCFG-reduction, which is heavily based on Goodman (2002). Goodman assigns every node in every tree a unique number which is called its address. The notation A@k denotes the node at address k where A is the nonterminal labeling that node. A new nonterminal is created for each node in the training data.

Background

acl_arc_intent_classification:train:1251

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Crystal (1969) claims that prosodic phrase boundaries will co-occur with grammatical functions such as subject, predicate, modifier, and adjunct. Both predicateargument relations and discourse factors have been examined for their possible input to prosodic phrasing. The syntax/prosody misalignment may be viewed as resulting in part from semantic considerations. Citation Sentence: Crystal ( 1969 ) claims that prosodic phrase boundaries will co-occur with grammatical functions such as subject , predicate , modifier , and adjunct . Context after the citation: Selkirk (1984) and Nespor and Vogel (1986) take a similar approach, but within a different theoretical framework. Previous versions of our work, as described in Bachenko et al. (1986) also assume that phrasing is dependent on predicate-argument structure. The problem here is that the phrasing in observed data often ignores the argument status of constituents. In 17a—f, for example, the phrasing makes no distinction between arguments and adjuncts.

Background

acl_arc_intent_classification:train:1252

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: We rephrase the method of Grimley-Evans (1997) as follows: First, we construct the approximating finite automaton according to the unparameterized RTN method above. Citation Sentence: We rephrase the method of Grimley-Evans ( 1997 ) as follows : First , we construct the approximating finite automaton according to the unparameterized RTN method above . Context after the citation: Then an additional mechanism is introduced that ensures for each rule A — Xi . X„, separately that the list of visits to the states go, , gni satisfies some reasonable criteria: a visit to g,, with 0 < i < m, should be followed by one to gi+i or go. The latter option amounts to a nested incarnation of the rule. There is a complementary condition for what should precede a visit to q,, with 0 < i < m.

Uses

acl_arc_intent_classification:train:1253

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: 6The analysis is reminiscent of the treatment of coordination in the Collins parser (Collins, 1999). In Turkish, very essential syntactic information is contained in the rich morphological structure, where Citation Sentence: 6The analysis is reminiscent of the treatment of coordination in the Collins parser ( Collins , 1999 ) . Context after the citation: concatenated suffixes carry information that in other languages may be expressed by separate words. The Turkish treebank therefore divides word forms into smaller units, called inflectional groups (IGs), and the task of the parser is to construct dependencies between IGs, not (primarily) between word forms (Eryi˘git and Oflazer, 2006). It is then important to remember that an unlabeled attachment score of 75.8% corresponds to a word-to-word score of 82.7%, which puts Turkish on a par with languages like Czech, Dutch and Spanish. Moreover, when we break down the results according to whether the head of a dependency is part of a multiple-IG word or a complete (single-IG) word, we observe a highly significant difference in accuracy, with only 53.2% unlabeled attachment score for multiple-IG heads versus 83.7% for single-IG heads.

CompareOrContrast

acl_arc_intent_classification:train:1254

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: The work is carried out in order to assist terminographers in the enrichment of a dictionary on computing that includes collocational information (L'Homme, 2004). In this paper, the method is applied to a French corpus on computing to find noun-verb combinations in which verbs convey a meaning of realization. The work reported here infers specific semantic relationships based on sets of examples and counterexamples. Citation Sentence: The work is carried out in order to assist terminographers in the enrichment of a dictionary on computing that includes collocational information ( L'Homme , 2004 ) . Context after the citation: Even though this work is carried out for terminographical and lexicographical purposes, it can certainly be of use in other applications, namely information retrieval. Indeed, such rich semantic links can be used to extend indices or reformulate queries (similar to the work by Voorhees (1994) with WoRDNET relations).

Motivation

acl_arc_intent_classification:train:1255

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: CornmandTalk (Moore et al., 1997), Circuit Fix-It Shop (Smith, 1997) and TRAINS-96 (Traum and Allen, 1994; Traum and Andersen, 1999) are spoken language systems but they interface to simulation or help facilities rather than semi-autonomous agents. A number of other systems have addressed part of the task. More recent work on spoken language interfaces to semi-autonomous robots include SRI's Flakey robot (Konolige et al., 1993) and NCARAI's InterBOT project (Perzanowski et al., 1998; Perzanowski et al., 1999). Citation Sentence: CornmandTalk ( Moore et al. , 1997 ) , Circuit Fix-It Shop ( Smith , 1997 ) and TRAINS-96 ( Traum and Allen , 1994 ; Traum and Andersen , 1999 ) are spoken language systems but they interface to simulation or help facilities rather than semi-autonomous agents . Context after the citation: Jack's MOOse Lodge (Badler et al., 1999) takes text rather than speech as natural language input and the avatars being controlled are not semi-autonomous. Other researchers have considered particular aspects of the problem such as accounting for various aspects of actions (Webber, 1995; Pym et al., 1995). In most of this and other related work the treatment is some variant of the following. If there is a speech interface, the input speech signal is converted into text.

Background

acl_arc_intent_classification:train:1256

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: The annotation procedure is dependent on locating the head daughter, for which an amended version of Magerman (1994) is used. The algorithm uses categorial, configurational, local head, and Penn-II functional and trace information. We utilize the automatic annotation algorithm of Cahill et al. (2002) and Cahill, McCarthy, et al. (2004) to derive a version of Penn-II in which each node in each tree is annotated with LFG functional annotations in the form of attribute-value structure equations. Citation Sentence: The annotation procedure is dependent on locating the head daughter , for which an amended version of Magerman ( 1994 ) is used . Context after the citation: The head is annotated with the LFG equation r=J.. Linguistic generalizations are provided over the left (the prefix) and the right (suffix) context of the head for each syntactic category occurring as the mother nodes of such heads. To give a simple example, the rightmost NP to the left of a VP head under an S is likely to be the subject of the sentence (r SUBJ =J.), while the leftmost NP to the right of the V head of a VP is most probably the verb’s object (r OBJ =J.). Cahill, McCarthy, et al. (2004) provide four classes of annotation principles: one for noncoordinate configurations, one for coordinate configurations, one for traces (long-distance dependencies), and a final “catch all and clean up” phase.

Uses

acl_arc_intent_classification:train:1257

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Riehemann 1993; Oliva 1994; Frank 1994; Opalka 1995; Sanfilippo 1995). In a number of proposals, lexical generalizations are captured using lexical underspecification (Kathol 1994; Krieger and Nerbonne 1992; Lexical rules have not gone unchallenged as a mechanism for expressing generalizations over lexical information. Citation Sentence: Riehemann 1993 ; Oliva 1994 ; Frank 1994 ; Opalka 1995 ; Sanfilippo 1995 ) . Context after the citation: The lexical entries are only partially specified, and various specializations are encoded via the type hierarchy, definite clause attachments, or a macro hierarchy. These approaches seem to propose a completely different way to capture lexical generalizations. It is therefore interesting that the covariation lexical rule compiler produces a lexicon encoding that, basically, uses an underspecification representation: The resulting definite clause representation after constraint propagation represents the common information in the base lexical entry, and uses a definite clause attachment to encode the different specializations. 8.

CompareOrContrast

acl_arc_intent_classification:train:1258

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: For instance, Divay and Vitale (1997) recently wrote: &quot;To our knowledge, learning algorithms, although promising, have not (yet) reached the level of rule sets developed by humans&quot; (p. 520). However, this possibility is not usually given much credence. It is also conceivable that data-driven techniques can actually outperform traditional rules. Citation Sentence: For instance , Divay and Vitale ( 1997 ) recently wrote : `` To our knowledge , learning algorithms , although promising , have not ( yet ) reached the level of rule sets developed by humans '' ( p. 520 ) . Context after the citation: Dutoit (1997) takes this further, stating &quot;such training-based strategies are often assumed to exhibit much more intelligence than they do in practice, as revealed by their poor transcription scores&quot; (p. 115, note 14). Pronunciation by analogy (PbA) is a data-driven technique for the automatic phonemization of text, originally proposed as a model of reading, e.g., by Glushko (1979) and Kay and Marcel (1981). It was first proposed for ITS applications over a decade ago by Dedina and Nusbaum (1986, 1991). See also the work of Byrd and Chodorow (1985), which considers computer-based pronunciation by analogy but does not mention the possible application to text-to-speech synthesis.

Background

acl_arc_intent_classification:train:1259

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: method Context before the citation: Table 1 gives the interpretations of eight adjective-noun combinations discussed in Pustejovsky (1995) and Vendler (1968). In what follows we explain the properties of the model by applying it to a small number of adjective-noun combinations taken from the lexical semantics literature. Citation Sentence: Table 1 gives the interpretations of eight adjective-noun combinations discussed in Pustejovsky ( 1995 ) and Vendler ( 1968 ) . Context after the citation: Table 2 shows the five most likely interpretations for these combinations as derived by the model discussed in the previous sections (v1 is the most likely interpretation, v2 is the second most likely interpretation, etc.). First notice that our model predicts variation in meaning when the same adjective modifies different nouns by providing different interpretations for easy problem and easy planet (see Table 2). Our model agrees with Vendler (1968) in the interpretation of easy problem (see Tables 1 and 2). Furthermore, it provides the additional meanings “a problem that is easy to deal with, identify, tackle, and handle”.

Uses

acl_arc_intent_classification:train:126

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Much previous work looks at the impact of using source side information (i.e., feature functions on the aligned English), such as those of Avramidis and Koehn (2008), Yeniterzi and Oflazer (2010) and others. So it is questionable as to whether morpheme segmentation techniques are sufficient to solve the inflectional problem we are addressing. In German these linguistic features are marked very irregularly and there is widespread syncretism, making it difficult to split off morphemes specifying these features. Citation Sentence: Much previous work looks at the impact of using source side information ( i.e. , feature functions on the aligned English ) , such as those of Avramidis and Koehn ( 2008 ) , Yeniterzi and Oflazer ( 2010 ) and others . Context after the citation: Toutanova et. al.’s work showed that it is most important to model target side coherence and our stem markup also allows us to access source side information. Using additional source side information beyond the markup did not produce a gain in performance. For compound splitting, we follow Fritzinger and Fraser (2010), using linguistic knowledge encoded in a rule-based morphological analyser and then selecting the best analysis based on the geometric mean of word part frequencies.

CompareOrContrast

acl_arc_intent_classification:train:1260

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: experiments Context before the citation: We use an in-house statistical tagger (based on (Church, 1988)) to tag the text in which the unknown word occurs. The first feature represents the part of speech of the word. These identify two features of the unknown word itself as well as two features for each of the two preceding and two following words. Citation Sentence: We use an in-house statistical tagger ( based on ( Church , 1988 ) ) to tag the text in which the unknown word occurs . Context after the citation: The tag set used is a simplified version of the tags used in the machinereadable version of the Oxford Advanced Learners Dictionary (OALD). The tag set contains just one tag to identify nouns. The second feature provides more informative tagging for specific parts of speech (these are referred to as 'detailed tags' (DETAG)). This tagset consists of the nine tags listed in Table 1.

Uses

acl_arc_intent_classification:train:1261

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Based on a computational grammar that associates natural language expressions with both a syntactic and a semantic representation, a paraphrastic gram'As we shall briefly discuss in section 4, the grammar is developed with the help of a meta-grammar (Candito, 1999) thus ensuring an additional level of abstraction. We chose to investigate an alternative research direction by aiming to develop a “paraphrastic grammar” that is, a grammar which captures the paraphrastic relations between linguistic structuress. On the other hand, the degree of descriptive abstraction offered by the list of inference or paraphrase rules they output is low. Citation Sentence: Based on a computational grammar that associates natural language expressions with both a syntactic and a semantic representation , a paraphrastic gram ` As we shall briefly discuss in section 4 , the grammar is developed with the help of a meta-grammar ( Candito , 1999 ) thus ensuring an additional level of abstraction . Context after the citation: The metagrammar is an abstract specification of the linguistic properties (phrase structure, valency, realisation of grammatical functions etc.) encoded in the grammar basic units. This specification is then compiled to automatically produce a specific grammar. mar is a grammar that moreover associates paraphrases with the same semantic representation. That is, contrary to machine learning based approaches which relate paraphrases via sentence patterns, the paraphrastic grammar approach relates paraphrases via a common semantic representation.

Uses

acl_arc_intent_classification:train:1262

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: There are very few reported attempts at corpus-based automation of help-desk responses (Carmel, Shtalhaim, and Soffer 2000; Lapalme and Kosseim 2003; Bickel and Scheffer 2004; Malik, Subramaniam, and Kaushik 2007). The process of composing a planned response for a new request is informed by probabilistic and lexical properties of the requests and responses in the corpus. In contrast, the techniques examined in this article are corpus-based and data-driven. Citation Sentence: There are very few reported attempts at corpus-based automation of help-desk responses ( Carmel , Shtalhaim , and Soffer 2000 ; Lapalme and Kosseim 2003 ; Bickel and Scheffer 2004 ; Malik , Subramaniam , and Kaushik 2007 ) . Context after the citation: eResponder, the system developed by Carmel, Shtalhaim, and Soffer (2000), retrieves a list of request–response pairs and presents a ranked list of responses to the user. If the user is unsatisfied with this list, an operator is asked to generate a new response. The operator is assisted in this task by the retrieval results: The system highlights the request-relevant sentences in the ranked responses. However, there is no attempt to automatically generate a single response.

CompareOrContrast

acl_arc_intent_classification:train:1263

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: introduction Context before the citation: Both tasks are performed with a statistical framework: the mention detection system is similar to the one presented in (Florian et al., 2004) and the coreference resolution system is similar to the one described in (Luo et al., 2004). It is these orthographic variations and complex morphological structure that make Arabic language processing challenging (Xu et al., 2001; Xu et al., 2002). derivational and inflectional process, most prepositions, conjunctions, pronouns, and possessive forms are attached to the Arabic surface word. Citation Sentence: Both tasks are performed with a statistical framework : the mention detection system is similar to the one presented in ( Florian et al. , 2004 ) and the coreference resolution system is similar to the one described in ( Luo et al. , 2004 ) . Context after the citation: Both systems are built around from the maximum-entropy technique (Berger et al., 1996). We formulate the mention detection task as a sequence classification problem. While this approach is language independent, it must be modified to accomodate the particulars of the Arabic language. The Arabic words may be composed of zero or more prefixes, followed by a stem and zero or more suffixes.

CompareOrContrast

acl_arc_intent_classification:train:1264

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: The disambiguation of person names in Web results is usually compared to two other Natural Language Processing tasks: Word Sense Disambiguation (WSD) (Agirre and Edmonds, 2006) and Cross-document Coreference (CDC) (Bagga and Baldwin, 1998). In this section we will discuss (i) the state of the art in Web People Search in general, focusing on which features are used to solve the problem; and (ii) lessons learnt from the WePS evaluation campaign where most approaches to the problem have been tested and compared. Citation Sentence: The disambiguation of person names in Web results is usually compared to two other Natural Language Processing tasks : Word Sense Disambiguation ( WSD ) ( Agirre and Edmonds , 2006 ) and Cross-document Coreference ( CDC ) ( Bagga and Baldwin , 1998 ) . Context after the citation: Most of early research work on person name ambiguity focuses on the CDC problem or uses methods found in the WSD literature. It is only recently that the web name ambiguity has been approached as a separate problem and defined as an NLP task Web People Search on its own (Artiles et al., 2005; Artiles et al., 2007). Therefore, it is useful to point out some crucial differences between WSD, CRC and WePS: • WSD typically concentrates in the disambiguation of common words (nouns, verbs, adjectives) for which a relatively small number of senses exist, compared to the hundreds or thousands of people that can share the same name.

Background

acl_arc_intent_classification:train:1265

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: related work Context before the citation: Our own work (Wang and Callison-Burch, 2011) extends the first idea to paraphrase fragment extraction on monolingual parallel and comparable corpora. Quirk et al. (2007) extract fragments using a generative model of noisy translations. Munteanu and Marcu (2006) extract subsentential translation pairs from comparable corpora using the log-likelihood-ratio of word translation probability. Citation Sentence: Our own work ( Wang and Callison-Burch , 2011 ) extends the first idea to paraphrase fragment extraction on monolingual parallel and comparable corpora . Context after the citation: Our current approach also uses word-word alignment, however, we use syntactic dependency trees to compute grammatical fragments. Our use of dependency trees is inspired by the constituent-tree-based experiments of Callison-Burch (2008).

Extends

acl_arc_intent_classification:train:1266

You will be presented with a citation segment from the section of an NLP research paper, as well as the context surrounding that citation. Classify the intent behind this citation by choosing from one of the following categories: - Background: provides context or foundational information related to the topic. - Extends: builds upon the cited work. - Uses: applies the methods or findings of the cited work. - Motivation: cites the work as inspiration or rationale for the research. - CompareOrContrast: compares or contrasts the cited work with others. - FutureWork: cites the work as a direction for future research. Your answer should be a single word from the following list of options: ["Background", "Extends", "Uses", "Motivation", "CompareOrContrast", "FutureWork"]. Do not include any other text in your response. Section Title: None Context before the citation: They proved to be useful in a number of NLP applications such as natural language generation (Iordanskaja et al., 1991), multidocument summarization (McKeown et al., 2002), automatic evaluation of MT (Denkowski and Lavie, 2010), and TE (Dinu and Wang, 2009). Paraphrase tables (PPHT) contain pairs of corresponding phrases in the same language, possibly associated with probabilities. 1http://www.statmt.org/wmt10/ Citation Sentence: They proved to be useful in a number of NLP applications such as natural language generation ( Iordanskaja et al. , 1991 ) , multidocument summarization ( McKeown et al. , 2002 ) , automatic evaluation of MT ( Denkowski and Lavie , 2010 ) , and TE ( Dinu and Wang , 2009 ) . Context after the citation: One of the proposed methods to extract paraphrases relies on a pivot-based approach using phrase alignments in a bilingual parallel corpus (Bannard and Callison-Burch, 2005). With this method, all the different phrases in one language that are aligned with the same phrase in the other language are extracted as paraphrases. After the extraction, pruning techniques (Snover et al., 2009) can be applied to increase the precision of the extracted paraphrases. In our work we used available2 paraphrase databases for English and Spanish which have been extracted using the method previously outlined.

Motivation

acl_arc_intent_classification:train:1267