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{
    "paper_id": "O15-2007",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T08:10:30.428309Z"
    },
    "title": "Cross-Linguistic Error Types of Misused Chinese Based on Learners' Corpora 1",
    "authors": [
        {
            "first": "Keiko",
            "middle": [],
            "last": "Mochizuki \uf02a",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "Tokyo University of Foreign Studies",
                "location": {}
            },
            "email": ""
        },
        {
            "first": "Hiroshi",
            "middle": [],
            "last": "Sano",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "Tokyo University of Foreign Studies",
                "location": {}
            },
            "email": "sano@tufs.ac.jp"
        },
        {
            "first": "Ya-Ming",
            "middle": [],
            "last": "Shen",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "Tokyo University of Foreign Studies",
                "location": {}
            },
            "email": "yamingshen@lingua-house.jp"
        },
        {
            "first": "Chia-Hou",
            "middle": [],
            "last": "Wu",
            "suffix": "",
            "affiliation": {},
            "email": ""
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "This paper presents an empirical study on the difficulties in learning Chinese as a second language based on learners' corpora written by native English speakers and native Japanese speakers at CEFR-based A2 and B1 levels. The first part of this paper will discuss the procedures for how to collect learners' corpora, proofread, establish an error tag system and annotate errors. Later it will focus on a significant difference in the production of \" \u4e00 + Classifier\" among the corpora of native English speakers and native Japanese speakers. The corpus of English native speakers displays an overuse of \" \u4e00 + Classifier\", even in an atelic context like a negative construction or a conditional construction where a \" \u4e00 + Classifier\" should not occur. On the other hand, the corpus of Japanese native speakers displays a lack of \" \u4e00 + Classifier\". This striking contrast is due to whether or not a determiner position exists in each language. Since English has a determiner position which accommodates an article, \"a/an, the\", \"this/that/my/your/~'s\", English-native learners tend to treat the \" \u4e00 + Classifier\" as an article although it does not appear in an atelic event structure. On the other hand, Japanese does not have any determiner position before a Noun Phrase, therefore it is assumed that 1 This project, entitled \"Construction of a Japanese-English-Chinese Online Error Corpus and development of English, Japanese and Chinese language pedagogy taking into account learners' native",
    "pdf_parse": {
        "paper_id": "O15-2007",
        "_pdf_hash": "",
        "abstract": [
            {
                "text": "This paper presents an empirical study on the difficulties in learning Chinese as a second language based on learners' corpora written by native English speakers and native Japanese speakers at CEFR-based A2 and B1 levels. The first part of this paper will discuss the procedures for how to collect learners' corpora, proofread, establish an error tag system and annotate errors. Later it will focus on a significant difference in the production of \" \u4e00 + Classifier\" among the corpora of native English speakers and native Japanese speakers. The corpus of English native speakers displays an overuse of \" \u4e00 + Classifier\", even in an atelic context like a negative construction or a conditional construction where a \" \u4e00 + Classifier\" should not occur. On the other hand, the corpus of Japanese native speakers displays a lack of \" \u4e00 + Classifier\". This striking contrast is due to whether or not a determiner position exists in each language. Since English has a determiner position which accommodates an article, \"a/an, the\", \"this/that/my/your/~'s\", English-native learners tend to treat the \" \u4e00 + Classifier\" as an article although it does not appear in an atelic event structure. On the other hand, Japanese does not have any determiner position before a Noun Phrase, therefore it is assumed that 1 This project, entitled \"Construction of a Japanese-English-Chinese Online Error Corpus and development of English, Japanese and Chinese language pedagogy taking into account learners' native",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Abstract",
                "sec_num": null
            }
        ],
        "body_text": [
            {
                "text": "The purposes of constructing the Learners' Error Corpora can be divided into two categories. The first is to discover the errors made by advanced-level learners since we assume that these errors reflect grammatical difficulties, significant differences in conceptual representation between the target language and the native language, and a different focus of representation despite relatively easy sentence structures. We believe that lexical/syntactic areas that are difficult to learn are caused by cases where the natural language system itself is difficult and where translation is difficult due to negative transfer. Clarifying these differences will lead to improvements in language teaching materials.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Objectives of Constructing the Learners' Error Corpus",
                "sec_num": "1."
            },
            {
                "text": "The second purpose of the research is to obtain new findings for comparative linguistics. The error analysis of cross-linguistic learners' corpora will enable us to distinguish language-specific error types based on the learners' native language and universal error types which occur regardless of the learners' native languages. Distinguishing these two features will also lead to the improvement of language teaching methodologies, especially those based on comparative perspectives between the learners' native language and the target language.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Objectives of Constructing the Learners' Error Corpus",
                "sec_num": "1."
            },
            {
                "text": "The characteristics of the data set of the 'Full Moon' Learner Corpus of Chinese at Tokyo University of Foreign Studies (henceforth 'Full Moon Corpus') are as follows: The 'Full Moon Corpus' has four key features : 1) compositions are written by experienced learners majoring in Chinese in Japan, 2) compositions go through an appropriate proofreading process conducted by university teachers, 3) errors and corresponding corrections are recorded, and 4) the detailed profiles of the learners are also recorded.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "The 'Full Moon' Learner Corpus of Chinese at Tokyo University of Foreign Studies",
                "sec_num": "2.1"
            },
            {
                "text": "There are two tag categories for misuse: Error and Modify. The Error tag indicates grammatical errors while the Modify tag indicates inappropriate use of expressions ( 'expression' tag), punctuation and Chinese characters as shown in Figure 1 .",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 234,
                        "end": 242,
                        "text": "Figure 1",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Error Tag Categories",
                "sec_num": "2.2"
            },
            {
                "text": "Interpretation Framework (error tags) Classification and in-text marking of syntactical, lexical, stylistic, rhetorical and notational misuses",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Error Tag Categories",
                "sec_num": "2.2"
            },
            {
                "text": "The Error tag consists of the following four sub-categories: Replace, Delete, Insert and Move. The Replace tag indicates the need to replace an error with another correct expression. The Delete tag indicates that deleting an error will lead to a correct expression. The Insert tag indicates that inserting a new expressions will lead to a correct expression. The Move tag indicates a word order error.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Figure 1. Misuse Tag System",
                "sec_num": null
            },
            {
                "text": "The Modify tag consists of the following three sub-categories: Expression, Punctuation and Chinese character. The Expression tag indicates that it is preferable to use another expression or that the misuse cannot be categorized as any one specific error. The Punctuation As subcategories of the error tag, we have designed the 74 tags as shown in (1) referring to the grammatical system in\u300e\u65b0\u7de8\u73fe\u4ee3\u6f22\u8a9e\u300f(\u5f35\u658c\u3001\u9f4a\u6eec\u63da\u7b49\uff0c2002: 273-467).",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Figure 1. Misuse Tag System",
                "sec_num": null
            },
            {
                "text": "(1) Tag ",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 4,
                        "end": 7,
                        "text": "Tag",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Figure 1. Misuse Tag System",
                "sec_num": null
            },
            {
                "text": "We use the 'TNR_Chinese Writing Correction2014' and 'TNR_Chinese Error Corpus Tagger2014' (2014) tools developed by \u4e8e\u5eb7(Yu Kang) and \u7530\u4e2d\u826f(Ryo Tanaka) for proofreading and annotation. The procedures are as follows. First, compositions written by learners in a WORD file are converted to text files. Next, errors and the corresponding corrections are added to the composition texts using the 'TNR_ Chinese Writing Correction 2014' system. The following figure 2 is an example of proofreading using 'TNR_ Chinese Writing Correction 2014'. The 'TNR_ Chinese Writing Correction 2014' system displayed in Figure 4 has two windows: the left window displays the composition text and the right window displays corrections. Each correction in the right window and its corresponding error expression in the left window are marked up in the same color for better visibility.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 597,
                        "end": 605,
                        "text": "Figure 4",
                        "ref_id": "FIGREF2"
                    }
                ],
                "eq_spans": [],
                "section": "Method of Proofreading and Annotation",
                "sec_num": "2.3"
            },
            {
                "text": "For annotation, 'TNR_Chinese Writing Correction2014' and 'TNR_Chinese Error Corpus Tagger2014' (2014) enable free creation of tags and the displaying of a tag list underneath the composition text as shown in Figure 3 .",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 208,
                        "end": 216,
                        "text": "Figure 3",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Method of Proofreading and Annotation",
                "sec_num": "2.3"
            },
            {
                "text": "The first step in annotating a composition is to designate the region of each misused expression in the composition text. The second step is to choose one of 'Replace \u66ff\u63db, Delete \u522a\u9664, Insert \u6dfb\u52a0, Move \u79fb\u52d5, Expression \u8868\u73fe, Punctuation \u6a19\u9ede\u7b26\u865f, Chinese Character \u932f \u5225\u5b57' and click on the appropriate button. This procedure enables annotations to be made automatically. The third step is to choose one of the error subcategories, e.g. 'Resultative Complement \u7d50 \u679c \u88dc \u8a9e '. This click-annotation system greatly reduces the burden of annotation. 'TNR_ Chinese Writing Correction 2014' also has the function to convert annotated data into XML data. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Figure 3. Annotation System: Tag Buttons",
                "sec_num": null
            },
            {
                "text": "We will discuss two significant error types in two learners' corpora by comparing The Full Moon Corpus written by Japanese native speakers at TUFS with the TOCFL learners' corpus of Chinese written by English native speakers (henceforth, TOCFL corpus) 2 . (\u5f35\u8389\u840d Chang Li-Ping:2013) ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Cross-linguistic Analysis of Errors",
                "sec_num": "3."
            },
            {
                "text": "One of the most significant error categories observable in The Full Moon Corpus is the lack of \" \u4e00 + Classifier( \u91cf \u8a5e )\" while the TOCFL Corpus displays an overuse of \" \u4e00 + Classifier(\u91cf\u8a5e)\".\u5f35\u8389\u840d Chang Li-Ping(2014:68) also indicates the same contrast between English-Native learners and Japanese-Native learners. Table 4 compares the frequency of \" \u4e00 + Classifier '-ge \u500b' \" in The Full Moon Corpus and the TOCFL Corpus. Table 4 shows an interesting contrast in the frequency of \"\u4e00\u500b\" between The TOCFL English-Native Learners' Corpus and The Full Moon Japanese-Native Learners' Corpus. The TOCFL English-Native Learners' Corpus displays a higher frequency than The Full Moon Japanese-Native Learners' Corpus. Upon conducting a chi squared test, a significant difference between the data sets was discovered (0.1%, x\u00b2=150.03, p=0.000).",
                "cite_spans": [
                    {
                        "start": 198,
                        "end": 214,
                        "text": "Li-Ping(2014:68)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [
                    {
                        "start": 310,
                        "end": 317,
                        "text": "Table 4",
                        "ref_id": "TABREF3"
                    },
                    {
                        "start": 417,
                        "end": 424,
                        "text": "Table 4",
                        "ref_id": "TABREF3"
                    }
                ],
                "eq_spans": [],
                "section": "Classifier Phrase(\u91cf\u8a5e\u77ed\u8a9e) \" \u4e00 + Classifier(\u91cf\u8a5e)\"",
                "sec_num": "3.1"
            },
            {
                "text": "Let us examine the lack of \" \u4e00 + Classifier(\u91cf\u8a5e)\" in The Full Moon Japanese-Native Learners' Corpus. The following examples (2) to (18) show that each sentence lacks the bracketed \" \u4e00 + Classifier\" in The Full Moon Japanese-Native Learners' Corpus. There are almost no examples of overuse of \" \u4e00 + Classifier\" in The Full Moon Japanese-Native Learners' Corpus.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Lack of \" \u4e00 + Classifier\" : Japanese Learners",
                "sec_num": "3.2"
            },
            {
                "text": "(2) Copula \"\u662f Shi\" Construction: The reason why it is very difficult for Japanese learners of Chinese to learn the principle of \" \u4e00 + Classifier\" is because Japanese grammar is insensitive to 'Boundedness' (\u6709\u754c\u6027) which controls the occurrence of \" \u4e00 + Classifier\". Shen(\u6c88\u5bb6\u714a) (1995) discusses the interaction between \" \u4e00 + Classifier\" and the concept of 'bounded ' and 'unbounded' events. Shen (1995) indicates that a \" \u4e00 + Classifier\" is necessary before a 'bounded' Noun Phrase(NP) in 'Telic' events as follows: Shen (1995) 's \"bounded/unbounded\" theory can explain why the following types, (4) Perfective Construction with \"-le \u4e86\", (5) GOAL in \"Give\" Construction and \"Become\" Construction, (6) Presentative Construction and (7) Resultative/Directional Verb Compound require \" \u4e00 + Classifier\" since all cases in (4)(5)(6)(7) have \"telicity\", the subcategory of \"bounded\" concept in the temporal structure. In (2) Copula \" \u662f Shi\" Judgement Construction and (3) Existential \"You \u6709 \" Construction , \" \u4e00 + Classifier\" often appears after \"\u662f Shi\" /\"You \u6709\". Both constructions have the following informational structure:",
                "cite_spans": [
                    {
                        "start": 264,
                        "end": 280,
                        "text": "Shen(\u6c88\u5bb6\u714a) (1995)",
                        "ref_id": null
                    },
                    {
                        "start": 361,
                        "end": 398,
                        "text": "' and 'unbounded' events. Shen (1995)",
                        "ref_id": null
                    },
                    {
                        "start": 512,
                        "end": 523,
                        "text": "Shen (1995)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Lack of \" \u4e00 + Classifier\" : Japanese Learners",
                "sec_num": "3.2"
            },
            {
                "text": "(15) \"\u662f Shi\"/ \"You \u6709\"Construction Topic \"\u662f Shi\" /\"You \u6709\" \" \u4e00 + Classifier\" NP 1)Informational Structure Old Information New Information 2) Boundedness Bounded",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Lack of \" \u4e00 + Classifier\" : Japanese Learners",
                "sec_num": "3.2"
            },
            {
                "text": "It is supposed that the NP with new information is a bounded entity, because the NP with new information is a focus in terms of cognition.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Lack of \" \u4e00 + Classifier\" : Japanese Learners",
                "sec_num": "3.2"
            },
            {
                "text": "We find the reverse phenomenon in The TOCFL English-Native Learners' Corpus: the overuse of \" \u4e00 + Classifier\". The following examples (16) to (23) show that the bracketed \" \u4e00 + Classifier\" should be deleted . Shen (1995) 's \"bounded/unbounded\" theory can also explain why \" \u4e00 + Classifier\" cannot appear in (16) to (23): all cases express atelic events and an entity in an atelic event should be unbounded. Shen (1995) indicates that a \" \u4e00 + Classifier\" cannot appear in the following atelic structures. ",
                "cite_spans": [
                    {
                        "start": 209,
                        "end": 220,
                        "text": "Shen (1995)",
                        "ref_id": null
                    },
                    {
                        "start": 407,
                        "end": 418,
                        "text": "Shen (1995)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Overuse of \" \u4e00 + Classifier(\u91cf\u8a5e)\" :English-Native Learners",
                "sec_num": "3.3"
            },
            {
                "text": "Special thanks are due to Professor Chang Li-Ping \u5f35\u8389\u840d and Professor Howard Hao-Jan Chen \u9673\u6d69 \u7136 at the Mandarin Training Center, National Taiwan Normal University for offering this learners' corpus and guiding our work with their detailed comments.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            }
        ],
        "back_matter": [
            {
                "text": "The contrast between the lack of \" \u4e00 + Classifier\" in The Full Moon Japanese-Native Learners' Corpus and the overuse of \" \u4e00 + Classifier\" in The TOCFL English-Native Learners' Corpus suggests a difference in Noun Phrase Structures in Chinese, English, and Japanese.Japanese syntax has no 'functional category', therefore there is no syntactic node (i.e. 'determiner') to accommodate a constituent like \"a/an, the\" while English has 'determiner' as Fukui (1995) proposes. This syntactic difference between English and Japanese causes the contrast between the lack and the overuse of \" \u4e00 + Classifier\" in Japanese-native learners and English-native learners.In addition, Ikegami (\u6c60\u4e0a) (1981), (2007) and Kageyama (\u5f71\u5c71) (1997 Kageyama (\u5f71\u5c71) ( ), (2002 suggest that Japanese is an \"unboundedness-oriented\" \"less-individualization\" type language in terms of having no grammatical category of number, ellipsis of subject/object, and no determiner node. This \"unboundedness-oriented\", \"less-individualization\" feature is reflected in second language acquisition of Chinese and English by Japanese learners. Since Japanese grammar has no syntactic strategy to individualize an entity/event, it is very difficult to acquire both the principle of \" \u4e00 + Classifier\" NP which appears in an bounded/individualized noun, and the usage of the articles \"a/an, the\" in English. According to \"NTNU/TUFS Sunrise Learners' Corpus of English\", the most frequent error category in the Japanese-native learners corpus is articles \"a/an, the\" as shown in \"TUFS Online Dictionary of Misused English\" : http://sano.tufs.ac.jp/lcshare/htdocs/?lang=english On the other hand, English is a \"boundedness-oriented\" \"high-individualization\" type language in terms of having an obligatory grammatical category of number, determiner node, and an obligatory subject/object. The reason why the English-native TOCFL corpus displays an overuse of \" \u4e00 + Classifier\" is because the principle of individualizing a noun is different between English and Chinese. Chinese cannot individualize a noun in an atelic unbounded event like a future event, a potential, a negation, a missed action or a conditional. On the other hand, in English, each noun is itself classified according to its property: countable or uncountable. The principle of individualization in English is not controlled by \"Bounded/Unbounded\" cognition.",
                "cite_spans": [
                    {
                        "start": 448,
                        "end": 460,
                        "text": "Fukui (1995)",
                        "ref_id": "BIBREF0"
                    },
                    {
                        "start": 690,
                        "end": 696,
                        "text": "(2007)",
                        "ref_id": null
                    },
                    {
                        "start": 701,
                        "end": 720,
                        "text": "Kageyama (\u5f71\u5c71) (1997",
                        "ref_id": null
                    },
                    {
                        "start": 721,
                        "end": 745,
                        "text": "Kageyama (\u5f71\u5c71) ( ), (2002",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Comparative Analysis of Error Types by Japanese Learners and English-Native Learners",
                "sec_num": "3.4"
            },
            {
                "text": "This paper introduced an empirical study on the difficulties in learning \" \u4e00 + Classifier(\u91cf \u8a5e)\" in Chinese based on learners' corpora written by English-native learners and Japanese -native learners at CEFR-based A2 and B1 level. The interesting contrast between The TOCFL English-native learner's corpus and The Full Moon Japanese learners' corpus is the overuse and the lack of \" \u4e00 + Classifier\".The overuse of \" \u4e00 + Classifier\" in the English-native TOCFL corpus is due to the overgeneralization by English-native learners of Chinese that \"a/an NP\" is equivalent to \" \u4e00 + Classifier\" NP. On the other hand, the lack of \" \u4e00 + Classifier\" in The Full Moon Japanese learners' corpus is due to the lack of individualization in terms of cognition in Japanese. The different features of the three languages are summarized below: This comparative research into cross-linguistic learners' corpora suggests that it is indispensable to explore the pedagogy of Chinese based on leaners' native language to develop more efficient and advanced learning science.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Conclusion",
                "sec_num": "4."
            }
        ],
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                "year": null,
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                "raw_text": "\u5f35\u8389\u840d(2013)\u3002TOCFL \u4f5c\u6587\u8a9e\u6599\u5eab\u7684\u5efa\u7f6e\u8207\u61c9\u7528\u3002\u8f09\u65bc\u5d14\u5e0c\u4eae\u3001\u5f35\u5bf6\u6797(\u4e3b\u7de8)\uff0c\u7b2c",
                "links": null
            }
        },
        "ref_entries": {
            "FIGREF0": {
                "type_str": "figure",
                "text": "on Learners' Corpora tag indicates the need for correction in view of the style of writing. The Chinese character tag indicates the misuse of a Chinese character.",
                "num": null,
                "uris": null
            },
            "FIGREF1": {
                "type_str": "figure",
                "text": "Figure 2. Proofreading System",
                "num": null,
                "uris": null
            },
            "FIGREF2": {
                "type_str": "figure",
                "text": "Digitization Framework (XML Data)",
                "num": null,
                "uris": null
            },
            "FIGREF3": {
                "type_str": "figure",
                "text": "Topic(Old Information) + \"\u662f Shi\"+ Comment(New Information)' a. \u6211\u8a8d\u7232\u9019\u662f(\u4e00\u7a2e)\u6709\u76ca\u7684\u611b\u597d\u3002 b. \u4f46\u662f\uff0c\u751f\u5b69\u5b50\u662f(\u4e00\u4ef6)\u4e0d\u7c21\u55ae\u7684\u4e8b\u3002 c. \u5f9e\u524d\u6211\u53bb\u904e\u4eac\u90fd\uff0c\u4eac\u90fd\u662f(\u4e00\u500b)\u5f88\u7f8e\u9e97\u7684\u5730\u65b9\u3002 d. \u4f46\u662f\uff0c\u627e\u5230\u597d\u5de5\u4f5c\u4e26\u4e0d\u662f(\u4e00\u4ef6)\u597d\u7684\u4e8b\u60c5\u3002 e. \u5c0f\u5b78\u751f\u8ddf\u4ed6\u5011\u4ea4\u6d41\u662f(\u4e00\u500b)\u597d\u6a5f\u6703\uff0c\u4f46\u662f\uff0c\u5b69\u5b50\u5011\u807d\u5f97\u61c2\u4ed6\u5011\u7684\u8ab2\u55ce\uff1f f. \u73fe\u5728\uff0c\u74b0\u5883\u554f\u984c\u662f\u4e16\u754c\u7684(\u4e00\u500b)\u5f88\u5927\u7684\u8ab2\u984c\u3002 (3) Existential \"You \u6709\" Construction a. \u6771\u5927\u548c\u6709(\u4e00\u500b)\u5f88\u5927\u7684\u516c\u5712---\u6771\u5927\u548c\u5357\u516c\u5712\uff0c\u9644\u8fd1\u4e5f\u6709(\u4e00\u689d)\u5c0f\u6cb3\u3002 b. \u9019\u53f0\u96fb\u8996\u9084\u6709(\u4e00\u500b)\u529f\u80fd,\u90a3\u5c31\u662f\u807d\u97f3\u6a02\u3002 (4) Perfective Construction with \"-le \u4e86\"",
                "num": null,
                "uris": null
            },
            "FIGREF5": {
                "type_str": "figure",
                "text": "Topic Noun in \"\u662f Shi\" construction: It seems that the interlanguage of Chinese created by English native speakers displays the following incorrect overgeneralization: (24) Overgeneralization by English-native learners of Chinese a/an NP = \" \u4e00 + Classifier\" NP",
                "num": null,
                "uris": null
            },
            "TABREF0": {
                "num": null,
                "type_str": "table",
                "text": "These compositions are proofread by Chinese native speakers with an MA. or Ph.D in linguistics/language education and sufficient experience in teaching Chinese at university level. Proofread compositions clearly indicate errors and corrections so that the errors can be identified within the respective sentences.",
                "content": "<table><tr><td>Academic</td><td>Level</td><td>Number of</td><td>Approximate</td><td>Number of</td></tr><tr><td>Year</td><td>Chinese Major Students</td><td>essays</td><td>number of words</td><td>students</td></tr><tr><td>2013</td><td>Advanced (4 th year) Intermediate (2 nd / 3 rd year)</td><td>95 132</td><td>45,500 51,200</td><td>35 58</td></tr><tr><td>2014</td><td>Advanced (4 th year) Intermediate (2 nd / 3 rd year)</td><td>21 34</td><td>12,500 25,100</td><td>23</td></tr></table>",
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                "content": "<table><tr><td colspan=\"2\">13 \u8cd3\u8a9e</td><td>\u96d9\u8cd3\u8a9e</td></tr><tr><td colspan=\"2\">14 \u88dc\u8a9e</td><td colspan=\"2\">\u7d50\u679c\u88dc\u8a9e, \u8da8\u5411\u88dc\u8a9e, \u53ef\u80fd\u88dc\u8a9e, \u7a0b\u5ea6\u88dc\u8a9e, \u60c5\u614b\u88dc\u8a9e, \u6578\u91cf\u88dc\u8a9e, \u4ecb\u8a5e,</td></tr><tr><td/><td/><td>\u77ed\u8a9e\u88dc\u8a9e</td></tr><tr><td colspan=\"2\">15 \u7591\u554f\u53e5</td><td colspan=\"2\">\u662f\u975e\u554f\u53e5, \u7279\u6307\u554f\u53e5, \u9078\u64c7\u554f\u53e5, \u6b63\u53cd\u554f\u53e5</td></tr><tr><td colspan=\"2\">16 \u53e5\u5f0f</td><td colspan=\"2\">\u4e3b\u8b02\u8b02\u8a9e\u53e5, \"\u628a\"\u5b57\u53e5, \"\u88ab\"\u5b57\u53e5, \u9023\u52d5\u53e5, \u5f37\u8abf\u53e5, \u517c\u8a9e\u53e5, \u4f7f\u5f79</td></tr><tr><td/><td/><td colspan=\"2\">\u53e5, \u5b58\u73fe\u53e5, \u6bd4\u8f03\u53e5,\"\u9023\"\u5b57\u53e5</td></tr><tr><td colspan=\"2\">17 \u8907\u53e5</td><td colspan=\"2\">\u4e26\u5217\u8907\u53e5\uff1a\u627f\u63a5\u8907\u53e5, \u905e\u9032\u8907\u53e5, \u9078\u64c7\u8907\u53e5, \u6ce8\u89e3\u8907\u53e5</td></tr><tr><td/><td/><td colspan=\"2\">\u66ff\u63db, \u79fb\u52d5 \u522a\u9664, \u6dfb\u52a0, \u504f\u6b63\u8907\u53e5\uff1a\u56e0\u679c\u8907\u53e5, \u689d\u4ef6\u8907\u53e5, \u8f49\u6298\u8907\u53e5, \u8b93\u6b65\u8907\u53e5, \u76ee\u7684\u8907\u53e5 Error</td></tr><tr><td/><td colspan=\"2\">Misuse</td><td>Modify</td><td>\u8868\u73fe, \u6a19\u9ede\u7b26\u865f, \u932f\u5225\u5b57</td></tr><tr><td/><td>\u5927\u5206\u985e</td><td/><td>\u5c0f\u5206\u985e</td></tr><tr><td>1</td><td>\u540d\u8a5e</td><td colspan=\"2\">\u6642\u9593\u540d\u8a5e, \u8655\u6240\u540d\u8a5e, \u65b9\u4f4d\u8a5e</td></tr><tr><td>2</td><td>\u6578\u8a5e</td><td/></tr><tr><td>3</td><td>\u91cf\u8a5e</td><td/></tr><tr><td>4</td><td>\u52d5\u8a5e</td><td colspan=\"2\">\u72c0\u614b\u52d5\u8a5e, \u52d5\u4f5c\u52d5\u8a5e, \u5b58\u73fe\u52d5\u8a5e, \u95dc\u4fc2\u52d5\u8a5e, \u80fd\u9858\u52d5\u8a5e, \u8da8\u5411\u52d5\u8a5e,</td></tr><tr><td/><td/><td>\u4f7f\u4ee4\u52d5\u8a5e</td></tr><tr><td/><td/><td colspan=\"2\">\u53ca\u7269\u52d5\u8a5e, \u4e0d\u53ca\u7269\u52d5\u8a5e, \u96d9\u8cd3\u52d5\u8a5e</td></tr><tr><td/><td/><td>\u91cd\u758a\u52d5\u8a5e</td></tr><tr><td>5</td><td>\u5f62\u5bb9\u8a5e</td><td/></tr><tr><td>6</td><td>\u526f\u8a5e</td><td colspan=\"2\">\u7a0b\u5ea6\u526f\u8a5e, \u7bc4\u570d\u526f\u8a5e, \u6642\u9593\u526f\u8a5e, \u60c5\u614b\u526f\u8a5e, \u5426\u5b9a\u526f\u8a5e, \u8a9e\u6c23\u526f\u8a5e,</td></tr><tr><td/><td/><td>\u95dc\u806f\u526f\u8a5e</td></tr><tr><td>7</td><td>\u4ee3\u8a5e</td><td colspan=\"2\">\u4eba\u7a31\u4ee3\u8a5e, \u6307\u793a\u4ee3\u8a5e, \u7591\u554f\u4ee3\u8a5e</td></tr><tr><td>8</td><td>\u9023\u8a5e</td><td/></tr><tr><td>9</td><td>\u4ecb\u8a5e</td><td/></tr><tr><td colspan=\"2\">10 \u52a9\u8a5e</td><td colspan=\"2\">\u7d50\u69cb\u52a9\u8a5e, \u6642\u614b\u52a9\u8a5e, \u6642\u5236\u52a9\u8a5e, \u6bd4\u6cc1\u52a9\u8a5e, \u8868\u6578\u52a9\u8a5e, \u5217\u8209\u52a9\u8a5e, \u8a9e\u6c23</td></tr><tr><td/><td/><td colspan=\"2\">\u52a9\u8a5e, \u5176\u4ed6\u52a9\u8a5e</td></tr><tr><td colspan=\"2\">11 \u77ed\u8a9e</td><td colspan=\"2\">\u91cf\u8a5e\u77ed\u8a9e, \u65b9\u4f4d\u77ed\u8a9e, \u4ecb\u8a5e\u77ed\u8a9e, \"\u7684\"\u5b57\u77ed\u8a9e</td></tr><tr><td colspan=\"2\">12 \u4e3b\u8a9e</td><td/></tr></table>",
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            },
            "TABREF2": {
                "num": null,
                "type_str": "table",
                "text": "",
                "content": "<table><tr><td>TOCFL (CEFR)</td><td>Number of</td><td>Number of Chinese</td><td>Number of</td></tr><tr><td/><td>Compositions</td><td>characters</td><td>Students</td></tr><tr><td>\u57fa\u790e(A2)</td><td>223</td><td>119,971</td><td>223</td></tr><tr><td>\u9032\u968e(B1)</td><td>344</td><td>31,852</td><td>344</td></tr></table>",
                "html": null
            },
            "TABREF3": {
                "num": null,
                "type_str": "table",
                "text": "",
                "content": "<table><tr><td/><td>CEFR Level</td><td>Number of</td><td>Occurrence of \"\u4e00\u500b\"</td></tr><tr><td/><td/><td>Chinese characters</td><td/></tr><tr><td>The TOCFL</td><td>B1</td><td>119,971</td><td>586 tokens</td></tr><tr><td>English-Native Learners' Corpus</td><td>A2</td><td>31,852</td><td>159 tokens</td></tr><tr><td/><td>Total</td><td>151,823</td><td>745 tokens</td></tr><tr><td/><td/><td/><td>1,490 Chinese characters</td></tr><tr><td>The Full Moon</td><td>A2-B1</td><td>134,094</td><td>385 tokens</td></tr><tr><td>Japanese-Native Learners' Corpus</td><td/><td/><td>770 Chinese characters</td></tr></table>",
                "html": null
            }
        }
    }
}