| { | |
| "paper_id": "O13-1021", | |
| "header": { | |
| "generated_with": "S2ORC 1.0.0", | |
| "date_generated": "2023-01-19T08:03:54.519194Z" | |
| }, | |
| "title": "A Corpus-driven Pattern Analysis in Locative Phrases: A Statistical Comparison of Co-appearing Concepts in Fixed Frames", | |
| "authors": [ | |
| { | |
| "first": "\u8d99\u9022\u6bc5", | |
| "middle": [], | |
| "last": "August", | |
| "suffix": "", | |
| "affiliation": { | |
| "laboratory": "", | |
| "institution": "National Chengchi University", | |
| "location": {} | |
| }, | |
| "email": "" | |
| }, | |
| { | |
| "first": "F", | |
| "middle": [ | |
| "Y" | |
| ], | |
| "last": "Chao", | |
| "suffix": "", | |
| "affiliation": { | |
| "laboratory": "", | |
| "institution": "National Chengchi University", | |
| "location": {} | |
| }, | |
| "email": "" | |
| }, | |
| { | |
| "first": "Siaw-Fong", | |
| "middle": [], | |
| "last": "\u937e\u66c9\u82b3", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Chung", | |
| "suffix": "", | |
| "affiliation": {}, | |
| "email": "sfchung@nccu.edu.tw" | |
| } | |
| ], | |
| "year": "", | |
| "venue": null, | |
| "identifiers": {}, | |
| "abstract": "This paper analyzes synonym groups appearing in fixed frames containing Chinese locative phrases such as [z\u00e1i noun phrase (yi /zhi) sh\u00e0ng/xi\u00e0/etc. bia n/mi\u00e0n/etc.] by using statistical methods. We collected locative phrases from Sketch Engine using 11 monosyllabic locative words and 5 locative compound-formation patterns, and we aligned these compounds with Chinese Synonym Forest [1] before clustering. Different noun phrases were mapped to their collocating synonym groups to as to enable mutual information comparisons between different combinations. When analyzing concept combinations, we used point-wise mutual information to compare two synonym groups, and adopt multivariate mutual information", | |
| "pdf_parse": { | |
| "paper_id": "O13-1021", | |
| "_pdf_hash": "", | |
| "abstract": [ | |
| { | |
| "text": "This paper analyzes synonym groups appearing in fixed frames containing Chinese locative phrases such as [z\u00e1i noun phrase (yi /zhi) sh\u00e0ng/xi\u00e0/etc. bia n/mi\u00e0n/etc.] by using statistical methods. We collected locative phrases from Sketch Engine using 11 monosyllabic locative words and 5 locative compound-formation patterns, and we aligned these compounds with Chinese Synonym Forest [1] before clustering. Different noun phrases were mapped to their collocating synonym groups to as to enable mutual information comparisons between different combinations. When analyzing concept combinations, we used point-wise mutual information to compare two synonym groups, and adopt multivariate mutual information", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
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| "section": "Abstract", | |
| "sec_num": null | |
| } | |
| ], | |
| "body_text": [ | |
| { | |
| "text": "(MMI) [2] to examine three groups. The results showed that behaviors of using suffixes and prefixes to forming locative nouns in different context (combination of 1 or 2 top level synonym groups), and the statistic results can be used in further analyzing locative nouns in different fields.", | |
| "cite_spans": [ | |
| { | |
| "start": 6, | |
| "end": 9, | |
| "text": "[2]", | |
| "ref_id": "BIBREF1" | |
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| "ref_spans": [], | |
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| "section": "", | |
| "sec_num": null | |
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| { | |
| "text": "Keywords: Chinese Locative Nouns, Chinese Synonym Forest, PMI, MMI. ", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
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| { | |
| "text": "Li", | |
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| "section": "\u4e00\u3001\u7dd2\u8ad6 \u65b9 \u4f4d \u540d \u8a5e \u8868 \u9054 \u4e86 \u5f9e \u67d0 \u500b \u53c3 \u8003 \u7269 \u4ef6 \u6216 \u4e8b \u9805 \u800c \u7522 \u751f \u7684 \u65b9 \u5411 \u8cc7 \u8a0a \u3002 \u5728 \u4e2d \u6587 \u88e1 \uff0c", | |
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| "text": "\uf03d \uf0b4 \uf03d \u908a\u754c \u7684 PMI \u82e5\u6211\u5011\u5c07 \" \u7684 \"-\" \u908a\u754c\" \u540c \u6642 \u6bd4 \u8f03 \u5176 \u5b83 \u4e09 \u500b \u8a5e \u7d44 \" \u8033\u8a9e\", \" \u6c7a\u8b70\" \u8207 \" \u4eba\u53e3\" \uff1a 30 . 7 ) \" \u8033\u8a9e \" ; \" \" ( \uf03d \u7684 PMI \u3001 53 . 5 ) \" \" ; \" \" ( \uf03d \u6c7a\u8b70 \u7684 PMI \u3001 33 . 3 ) \" \" ; \" \" ( \uf03d \u4eba\u53e3 \u7684 PMI", | |
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| "section": "\u4e00\u3001\u7dd2\u8ad6 \u65b9 \u4f4d \u540d \u8a5e \u8868 \u9054 \u4e86 \u5f9e \u67d0 \u500b \u53c3 \u8003 \u7269 \u4ef6 \u6216 \u4e8b \u9805 \u800c \u7522 \u751f \u7684 \u65b9 \u5411 \u8cc7 \u8a0a \u3002 \u5728 \u4e2d \u6587 \u88e1 \uff0c", | |
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| "text": "\u539f\u5247\u53ef\u4ee5\u8b93\u6211\u5011\u4e86\u89e3\u5728\u7279\u5b9a\u7684\u8a9e\u6599\u5eab\u4e2d\uff0c\u4efb\u5169\u8a5e\u7d44\u4e4b\u9593\u5171\u540c\u51fa\u73fe\u7684\u76f8\u4f9d\u95dc\u4fc2\u3002\u800c\u6b64\u7279\u5b9a \u8a9e\u6599\u5eab\u4ea6\u53ef\u4f7f\u7528\u6709\u9650\u5236\u7684\u65b9\u4f4d\u8a5e\u66ff\u4ee3\u4e4b\uff0c\u4ee5\u4e86\u89e3\u5728\u65b9\u4f4d\u8a5e\u9650\u5236\u4e4b\u4e0b\u5169\u7279\u5b9a\u8a5e\u7d44\u7684\u5171\u540c\u51fa \u95dc\u4fc2\u60c5\u6cc1\u3002 (2)Multivariate Mutual Information \u5728\u4f7f\u7528 PMI \u8a08\u7b97\u76f8\u95dc\u6027\u6642\u6709\u4e00\u9650\u5236\u662f\uff0c\u50c5\u80fd\u8a08\u7b97\u5169\u5169\u6982\u5ff5\u6216\u8a5e\u7d44\u4e4b\u9593\u7684\u76f8\u95dc\u6027\u3002\u7576\u9762 \u81e8\u4e09\u500b(\u6216\u4e09\u500b\u4ee5\u4e0a)\u4e8b\u4ef6\u7684\u76f8\u95dc\u6027\u6bd4\u8f03\u6642\uff0c\u5247\u662f\u900f\u904e\u689d\u4ef6\u4e92\u65a5\u8cc7\u8a0a(Conditional Mutual Information)\u503c\u4f86\u9032\u884c\u64f4\u5c55\u3002\u6211\u5011\u4ee5\u4e09\u500b\u4e8b\u4ef6\u7684\u4e92\u65a5\u8cc7\u8a0a\u70ba\u4f8b\uff0c\u5b83\u7684\u6578\u503c\u7bc4\u570d\u5982\u4e0b[11]\uff1a )} ; ( ), ; ( ), ; ( min{ ) ; ; ( )} | ; ( ), | ; ( ), | ; ( min{ Z X I Z Y I Y X I Z Y X I Y Z X I X Z Y I Z Y X I \uf0a3 \uf0a3 \uf02d \u5176\u4e2d\uff0c ) | ; ( Z Y X I \u3001 ) | ; ( X Z Y I \u3001 ) | ; ( Y Z X I \u5247\u662f\u5404\u5225\u5728 Z, X, Y \u689d\u4ef6\u4e0b\uff0c\u8a08\u7b97 PMI(X;Y), PMI(Y;Z), PMI(X;Z)\u7684\u6578\u503c\u4e4b\u5f8c\u518d\u53d6\u6700\u5c0f\u503c\uff0c\u4e26\u8207\u5728\u7e3d\u9ad4\u6a23\u672c\u4e0b\u518d\u8a08\u7b97\u4e00\u6b21 PMI(X;Y), PMI(Y;Z), PMI(X;Z)\u3002\u9019\u6a23\u7684\u8a08\u7b97\u8981\u7d93\u904e 2 n -1 \u6b21\uff0c\u5341\u5206\u8907\u96dc\u3002\u5f9e\u800c\u6211\u5011\u53c3\u8003[2]\u7684\u591a\u8b8a\u6578 \u8cc7\u8a0a\u4e92\u65a5\u8a08\u7b97\u65b9\u6cd5\u4e2d\u7684\u5177\u9ad4\u4ea4\u4e92\u8cc7\u8a0a(SI 1 , Specific Interaction Information)\uff0c\u505a\u70ba\u4e09\u500b\u4e8b \u4ef6\u76f8\u95dc\u6027\u7684\u6bd4\u8f03\u539f\u5247\u3002\u5728[2]\u7684\u8a08\u7b97\u4e2d\uff0c\u5c07\u4e0a\u5f0f\u4e2d\u6c42\u591a\u8b8a\u6578\u4e92\u65a5\u8cc7\u8a0a\u503c ) ; ; ( Z Y X I \u5316\u7c21\u70ba \u4ea4\u4e92\u8cc7\u8a0a(SI 1 )\u7684\u4e00\u822c\u5f0f\u70ba\uff1a ) , , ( ) ( ) ( ) ( ) , ( ) , ( ) , ( log ) ; ; ( 1 z y x p z p y p x p z x p z y p y x p Z Y X SI \uf03d \u5f9e\u800c\u6b64 SI 1 \u5373\u53ef\u7528\u65bc\u4e09\u500b(\u6216\u4e09\u500b\u4ee5\u4e0a)\u7684\u4e8b\u4ef6\u76f8\u95dc\u5206\u6790\u4e4b\u4e2d\u3002\u5728\u6b64\u8981\u7279\u5225\u8aaa\u660e\uff0c\u5728[2]\u4e2d", | |
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| "section": "\u4e00\u3001\u7dd2\u8ad6 \u65b9 \u4f4d \u540d \u8a5e \u8868 \u9054 \u4e86 \u5f9e \u67d0 \u500b \u53c3 \u8003 \u7269 \u4ef6 \u6216 \u4e8b \u9805 \u800c \u7522 \u751f \u7684 \u65b9 \u5411 \u8cc7 \u8a0a \u3002 \u5728 \u4e2d \u6587 \u88e1 \uff0c", | |
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| "text": "\u7269) \u8ca0\u8cac(H-\u6d3b\u52d5) \u63a5\u53d7(H-\u6d3b\u52d5) \u4ee5\u4e0a\"\u3001 \"\u7c21\u5831(D-\u62bd\u8c61\u4e8b\u7269) \u5f8c(E-\u7279\u5fb5) \u4f5c(H-\u6d3b\u52d5) \u4ee5\u4e0a\"\u3001 \"\u76ee\u6a19(D-\u62bd\u8c61\u4e8b\u7269) \u6642(K-\u52a9\u8a9e) \u4f5c(H-\u6d3b\u52d5) \u4ee5\u4e0a\"\u3002\u6240\u4ee5\u6211\u5011\u53ef\u4ee5\u77e5\u4e3b\u8981\"\u4ee5\u4e0a\" \u90fd\u662f\u7528\u5728\u63cf\u8ff0\u6d3b\u52d5\u7684\u8a5e\u7d44\u65b9\u4f4d\u6027\u3002\u4e14\u5728\"\u4e0a\"\u7d44\u5408\u6a21\u5f0f\u4e4b\u4e2d\uff0c\u50c5\"\u4ee5\u4e0a\"\u7684\"(H-\u6d3b\u52d5)\"\u4f7f\u7528 \u60c5\u6cc1\u8f03\u5176\u5b83\u524d\u98fe\u5f8c\u7db4\u7684\u65b9\u4f4d\u7528\u8a9e\u7d44\u5408\u4f86\u8aaa\u8f03\u70ba\u56fa\u5b9a\u3002\u65b9\u4f4d\u8a5e\"\u4e0b\"\u53ef\u5206\u6210\"\u4e0b\u9762\"\u8207\"\u4ee5 \u4e0b\"/\"\u4e0b\u908a\"\u5169\u7a2e\u985e\u5225\uff0c\u5176\u4e2d\"\u4e0b\u9762\"\u7684\u60c5\u6cc1\u8f03\u56fa\u5b9a\u7684\u7d44\u5408\u6a21\u5f0f\u662f\" (J-\u95dc\u806f) 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| "cite_spans": [], | |
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| "eq_spans": [], | |
| "section": "\u62bd\u8c61\u4e8b\u7269) (H-\u6d3b\u52d5)\u6216(E-\u7279\u5fb5)\u6216(K-\u52a9\u8a9e) (H-\u6d3b\u52d5) \u4ee5\u4e0a\"\uff0c\u5176\u4e2d\"(H-\u6d3b\u52d5)\u6216(E-\u7279\u5fb5)\u6216 (K-\u52a9\u8a9e) (H-\u6d3b\u52d5)\"\u7d44\u5408\u6a21\u5f0f\u662f(H-\u6d3b\u52d5)\u8a5e\u7d44\u7684\u660e\u78ba\u6027(specific)\u8aaa\u660e\uff0c\u5982\"\u7d44\u7e54(D-\u62bd\u8c61\u4e8b", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "Proceedings of the Twenty-Fifth Conference on Computational Linguistics and Speech Processing(ROCLING 2013)", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "", | |
| "sec_num": null | |
| }, | |
| { | |
| "text": "\u4e2d\u6587\u5341\u5104\u5b57\u8a9e\uf9be\u5eab\u5305\u62ec\u4e86 2466840 \u7bc7\u53f0\u7063\u4e2d\u592e\u793e(CNA)\u8207\u5927\u9678\u65b0\u83ef\u793e(XIN)\u65b0\u805e\u6587\u672c\u3002 Proceedings of the Twenty-Fifth Conference on Computational Linguistics and Speech Processing (ROCLING 2013)", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "", | |
| "sec_num": null | |
| } | |
| ], | |
| "back_matter": [ | |
| { | |
| "text": "This research is supported by National Science Council grant 101-2410-H-004-176-MY2 directed by Siaw-Fong Chung.Proceedings of the Twenty-Fifth Conference on Computational Linguistics and Speech Processing (ROCLING 2013)", | |
| "cite_spans": [], | |
| "ref_spans": [], | |
| "eq_spans": [], | |
| "section": "Acknowledgements", | |
| "sec_num": null | |
| } | |
| ], | |
| "bib_entries": { | |
| "BIBREF1": { | |
| "ref_id": "b1", | |
| "title": "Two Multivariate Generalizations of Pointwise Mutual Information", | |
| "authors": [ | |
| { | |
| "first": "T", | |
| "middle": [], | |
| "last": "Cruys", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "", | |
| "middle": [], | |
| "last": "Van De", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2011, | |
| "venue": "Proceedings of the Workshop on Distributional Semantics and Compositionality (DiSCo'2011)", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "16--20", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Cruys, T. Van de, \"Two Multivariate Generalizations of Pointwise Mutual Information\", Proceedings of the Workshop on Distributional Semantics and Compositionality (DiSCo'2011), pp. 16-20, 2011.", | |
| "links": null | |
| }, | |
| "BIBREF2": { | |
| "ref_id": "b2", | |
| "title": "Mandarin Chinese: A functional reference grammar", | |
| "authors": [ | |
| { | |
| "first": "C", | |
| "middle": [ | |
| "N" | |
| ], | |
| "last": "Li", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S", | |
| "middle": [ | |
| "A" | |
| ], | |
| "last": "Thompson", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 1989, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Li, C. N. and Thompson, S. A., \"Mandarin Chinese: A functional reference grammar\", University of California Press, 1989.", | |
| "links": null | |
| }, | |
| "BIBREF8": { | |
| "ref_id": "b8", | |
| "title": "A Lexico-Semantic Analysis of Chinese Locality Phrases -A Topic Clustering Approach", | |
| "authors": [ | |
| { | |
| "first": "A", | |
| "middle": [], | |
| "last": "Chao", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "S", | |
| "middle": [ | |
| "F" | |
| ], | |
| "last": "Chung", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": null, | |
| "venue": "Forthcoming in Generative Lexicon and Distributional Semantics 6th International Conference", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Chao, A. and Chung, S. F., \"A Lexico-Semantic Analysis of Chinese Locality Phrases -A Topic Clustering Approach\", Forthcoming in Generative Lexicon and Distributional Semantics 6th International Conference, Italy.", | |
| "links": null | |
| }, | |
| "BIBREF9": { | |
| "ref_id": "b9", | |
| "title": "Uniform and effective tagging of a heterogeneous giga-word corpus", | |
| "authors": [ | |
| { | |
| "first": "W", | |
| "middle": [ | |
| "Y" | |
| ], | |
| "last": "Ma", | |
| "suffix": "" | |
| }, | |
| { | |
| "first": "C", | |
| "middle": [ | |
| "R" | |
| ], | |
| "last": "Huang", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2006, | |
| "venue": "5th International Conference on Language Resources and Evaluation (LREC2006)", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "24--28", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Ma, W. Y. and Huang, C. R., \"Uniform and effective tagging of a heterogeneous giga-word corpus\", In 5th International Conference on Language Resources and Evaluation (LREC2006), pp. 24-28, 2006.", | |
| "links": null | |
| }, | |
| "BIBREF10": { | |
| "ref_id": "b10", | |
| "title": "A review on multivariate mutual information", | |
| "authors": [ | |
| { | |
| "first": "S", | |
| "middle": [], | |
| "last": "Sunil", | |
| "suffix": "" | |
| } | |
| ], | |
| "year": 2008, | |
| "venue": "", | |
| "volume": "", | |
| "issue": "", | |
| "pages": "", | |
| "other_ids": {}, | |
| "num": null, | |
| "urls": [], | |
| "raw_text": "Sunil, S., \"A review on multivariate mutual information\", Univ. of Notre Dame, Notre Dame, Indiana, 2008.", | |
| "links": null | |
| } | |
| }, | |
| "ref_entries": { | |
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| "type_str": "figure", | |
| "text": "A~L \u662f\u540c\u7fa9\u8a5e\u985e\u4ee3\u865f\u4e2d\u7684\u7b2c\u4e00\u78bc\uff0c\u5206\u5225\u70ba\u4eba(A)\u3001\u7269(B)\u3001\u6642\u9593/\u7a7a\u9593(C)\u3001\u62bd\u8c61 \u4e8b\u7269(D)\u3001\u7279\u5fb5(E)\u3001\u52d5\u4f5c(F)\u3001\u5fc3\u7406\u6d3b\u52d5(G)\u3001\u6d3b\u52d5(H)\u3001\u73fe\u8c61\u8207\u72c0\u614b(I)\u3001\u95dc\u806f(J)\u3001\u8a9e\u52a9(K)\u3001 \u656c\u8a9e(L)\u7b49\u5341\u4e8c\u7d44\u5927\u985e\u3002\u5728\u6bcf\u5f35\u5b50\u8868\u7684\u5de6\u65b9\u8ef8\u662f\u8ddd\u96e2\u65b9\u4f4d\u540d\u8a5e\u4e8c\u500b\u4f4d\u7f6e\u7684\u8a5e\u7d44(\u5373 window size \u70ba-2\uff0c\u5f80\u524d\u6578\u7b2c\u4e8c\u500b\u8a5e\u7d44) \uff0c\u800c\u4e0a\u9762\u8ef8\u662f\u8ddd\u96e2\u65b9\u4f4d\u540d\u8a5e\u4e00\u500b\u4f4d\u7f6e\u7684\u8a5e\u7d44(\u5373 window size \u70ba-1\uff0c\u5f80\u524d\u6578\u7b2c\u4e00\u500b\u8a5e\u7d44) \u3002\u6240\u4ee5\u6211\u5011\u7528\"\u4e0a\"\u5b50\u8868\u70ba\u4f8b\uff0c\u5de6\u65b9\u70ba A \u4e0a\u65b9\u70ba A \u7684\u4ea4\u96c6\u51fa\u73fe\"\u4ee5\" \u7684\u60c5\u6cc1\uff0c\u662f\u8868\u793a\u65b9\u4f4d\u77ed\u8a9e\u7d44\u5408\u5fc5\u9700\u662f\u7b2c\u4e00\u7d44(\u65b9\u4f4d\u540d\u8a5e\u524d\u4e8c\u4f4d\u7f6e)\u70ba\u4eba\u8a5e\u985e\u4e4b\u4e0b\u7684\u8a5e\u7d44\u8207 \u7b2c\u4e8c\u7d44(\u65b9\u4f4d\u540d\u8a5e\u524d\u4e00\u4f4d\u7f6e)\u4ea6\u70ba\u4eba\u8a5e\u985e\u4e4b\u4e0b\u7684\u8a5e\u7d44\uff0c\u6700\u5f8c\u65b9\u4f4d\u540d\u8a5e\u7684\u70ba\"\u4ee5\u4e0a\"\u7684\u60c5\u6cc1\uff0c \u4f8b\u5982\uff1a\"\u52a9\u7406(A-\u4eba) \u6559\u6388(A-\u4eba) \u4ee5\u4e0a\"\u3001 \"\u4e3b\u4efb(A-\u4eba) \u6aa2\u5bdf\u5b98(A-\u4eba) \u4ee5\u4e0a\"\u7684\u65b9\u4f4d\u77ed\u53e5\u3002 Proceedings of the Twenty-Fifth Conference on Computational Linguistics and Speech Processing (ROCLING 2013) \u8868 5 \u5305\u62ec\u5169\u6982\u5ff5\u7684\u65b9\u4f4d\u8a5e\u7d44\u6210\u76f8\u95dc\u8868", | |
| "num": null | |
| }, | |
| "TABREF1": { | |
| "text": "Proceedings of the Twenty-Fifth Conference on Computational Linguistics and Speech Processing(ROCLING 2013)", | |
| "content": "<table><tr><td colspan=\"5\">\u4ea6\u5b9a\u7fa9 SI 2 \u5b9a\u70ba\u5177\u9ad4\u76f8\u95dc\u6027\uff0c\u4f46\u5728\u6b64\u4e0d\u4f7f\u7528\u7684\u539f\u56e0\u662f\uff1aSI 2 \u662f\u7528\u5c07\u591a\u500b\u4e8b\u4ef6\u8996\u70ba\u4e00\u500b\u6574\u9ad4 \u4e4b\u4e2d\u7684\u5341\u5104\u5b57\u4e2d\u6587\u8a9e\u6599\u5eab\u5c0b\u627e\u6709\u51fa\u73fe\u5f85\u5c0b\u627e\u7684\u65b9\u4f4d\u540d\u8a5e\u7d44\u3002\u5f85\u64f7\u53d6\u5b8c\u6210\u6240\u6709\u7684\u8cc7\u6599\u4e4b \u7d44\u4ee3\u78bc\u3002\u5728\u9019\u88e1\uff0c\u6211\u5011\u70ba\u6c42\u80fd\u7cbe\u78ba\u5730\u627e\u5230\u6982\u5ff5\u9593\u7684\u7d44\u5408\uff0c\u6240\u4ee5\u6211\u5011\u5247\u4ee5\u6392\u5217\u7d44\u5408\u7684\u65b9\u5f0f</td></tr><tr><td colspan=\"5\">\u5c0d\u7279\u5b9a\u60c5\u5883\u7684\u76f8\u95dc\u6027\uff0c\u4e00\u822c\u662f\u4f7f\u7528\u5728\u8cc7\u8a0a\u6316\u6398(Information Retrieval)\u9818\u57df\u4e2d\u5c6c\u6027\u9078\u64c7 \u5f8c\uff0c\u6211\u5011\u5148\u9032\u884c\u8a08\u7b97\u4e0d\u540c\u65b9\u4f4d\u540d\u8a5e\u7d44\u5408\u7684\u6558\u8ff0\u7d71\u8a08\u7d50\u679c\uff0c\u4ee5\u9a57\u8b49\u6f22\u8a9e\u6587\u6cd5\u4e0a\u7684\u524d\u98fe/\u5f8c \u5c07\u6240\u6709\u53ef\u80fd\u7684\u7d44\u5408\u60c5\u6cc1\u90fd\u7f85\u5217\u5728\u5167\u3002\u6700\u5f8c\u8a08\u7b97\u6982\u5ff5\u95dc\u806f\u6642\uff0c\u5247\u6703\u4f9d\u4ee3\u78bc\u7d44\u5408\u7684\u6578\u76ee\u9010\u4e00</td></tr><tr><td colspan=\"5\">(feature selection)\u65b9\u6cd5\u4e0a\u3002\u800c\u672c\u7814\u7a76\u88e1\u7684\u53d6\u5f97\u7684\u65b9\u5411\u77ed\u53e5\u90fd\u662f\u5177\u9ad4\u4f7f\u7528\u5230\u7279\u5b9a\u7684\u65b9\u5411\u540d \u7db4\u7d44\u5408\u6587\u6cd5\u60c5\u6cc1\u3002\u7136\u5f8c\u6211\u5011\u4fbf\u9032\u884c\u77ed\u53e5\u7684\u904e\u6ffe\uff0c\u5c07\u65b9\u4f4d\u540d\u8a5e\u77ed\u53e5\u5207\u5272\u51fa\u4f86\uff0c\u6700\u5f8c\u900f\u904e\u540c \u8a08\u7b97\u4e92\u65a5\u8cc7\u8a0a\u8a08\u7b97\u516c\u5f0f\u3002\u5728\u8a08\u7b97\u6982\u5ff5\u95dc\u806f\u6027\u6642\uff0c\u4ee5\u9ad8\u968e\u5c64\u77e5\u8b58\u6982\u5ff5\u70ba\u57fa\u6e96\uff0c\u5373\u5c07\u53d6\u5f97\u7684 \u8a5e\uff0c\u5373\u6240\u6709\u77ed\u53e5\u88e1\u7684\u8a5e\u7d44\u5728\u8a9e\u6599\u5eab\u4e2d\u90fd\u662f\u6211\u5011\u8981\u7814\u7a76\u7684\u5c0d\u8c61\uff0c\u4e26\u6c92\u6709\u8a5e\u7d44\u9078\u64c7\u4e0a\u7684\u554f\u984c\u3002 \u7fa9\u8a5e\u8a5e\u6797\u9032\u884c\u540c\u7fa9\u8a5e\u7d44\u4ee3\u78bc\u8f49\u63db\uff0c\u5b8c\u6210\u8cc7\u6599\u6e05\u7406\u7684\u52d5\u4f5c\u3002 \u8a5e\u7d44\u4ee3\u78bc\u4ee5\u7b2c\u4e00\u78bc(\u5373 A~L)\u9032\u884c\u8a08\u7b97\uff0c\u4ee5\u5f97\u5230\u4e00\u822c\u6027\u6982\u5ff5\u5728\u65b9\u4f4d\u77ed\u53e5\u4e2d\u7684\u7d44\u6210\u6a21\u5f0f\u3002</td></tr><tr><td colspan=\"5\">(\u4e8c)\u540c\u7fa9\u8a5e\u8a5e\u6797 \u540c\u7fa9\u8a5e\u8a5e\u6797(\u6885\u5bb6\u99d2\u7b49,1983)\u6536\u9304\u4f86\u81ea\u8a5e\u7d20\u3001\u8a5e\u7d44\u3001\u6210\u8a9e\u3001\u65b9\u8a00\u8a5e\u8207\u53e4\u8a9e\u7b49\u8a5e\u7b49\u5171\u4e94\u842c\u4e09 \u5728\u5efa\u7acb\u5f85\u5c0b\u627e\u7684\u65b9\u4f4d\u540d\u8a5e\u7d44\u6642\uff0c\u6211\u5011\u6bd4\u8f03\u8868 1 \u4e2d\u6587\u65b9\u4f4d\u591a\u97f3\u8a5e\u7d44\u5408\u8868\u4e2d\u7684\u7d44\u5408\u5167\u5bb9\u3002\u7814 \u7a76\u904e\u7a0b\u4e2d\uff0c\u6211\u5011\u9664\u6389\u5de6\u3001\u53f3\u3001\u5167\u3001\u4e2d\u7684\u65b9\u4f4d\u540d\u8a5e\uff0c\u56e0\u70ba\u5f9e\u8868 1 \u4e2d\u53ef\u77e5\u6b64 4 \u500b\u65b9\u4f4d\u55ae\u97f3\u540d (\u4e8c)\u7814\u7a76\u7d50\u679c</td></tr><tr><td colspan=\"5\">\u5343\u591a\u8a5e\u5f59\u6578\uff0c\u4e26\u4e14\u4f9d\u7167\u540c\u7fa9\u8a5e\u5206\u985e\u6db5\u7fa9\u6709\u7cfb\u7d71\u5730\u5340\u5206\u70ba\u4eba(A)\u3001\u7269(B)\u3001\u6642\u9593/\u7a7a\u9593(C)\u3001 \u62bd\u8c61\u4e8b\u7269(D)\u3001\u7279\u5fb5(E)\u3001\u52d5\u4f5c(F)\u3001\u5fc3\u7406\u6d3b\u52d5(G)\u3001\u6d3b\u52d5(H)\u3001\u73fe\u8c61\u8207\u72c0\u614b(I)\u3001\u95dc\u806f(J)\u3001\u8a9e \u52a9(K)\u3001\u656c\u8a9e(L)\u7b49\u5341\u4e8c\u7d44\u5927\u985e\u4ee5\u53ca\u82e5\u5e72\u4e2d\u985e\u8207\u5c0f\u985e\u3002\u540c\u985e\u578b\u8a5e\u8a9e\u4f9d\u7167\u300c\u76f8\u5c0d\u3001\u6bd4\u8f03\u300d\u7684 \u5728\u524d\u8ff0\u7684\u8a08\u7b97\u904e\u7a0b\uff0c\u6211\u5011\u5148\u5c0d\u53d6\u5f97\u7684\u8a9e\u6599\u9032\u884c\u521d\u6b65\u7684\u6558\u8ff0\u7d71\u8a08\u8a0e\u8ad6\u5f8c\uff0c\u518d\u5c0d\u4e0d\u540c\u7684\u77e5\u8b58 \u8a5e\u7684\u7d44\u5408\u51fa\u73fe\u8f03\u5c11(\u5373\u5de6/\u53f3\u552f\u6709\u5f8c\u7db4\u7528\u6cd5\u3001\u5167/\u4e2d\u50c5\u6709\u524d\u98fe\u7528\u6cd5)\u3002\u5728\u9032\u884c\u64f7\u53d6\u7684\u904e\u7a0b\u88e1\uff0c \u6982\u5ff5\u95dc\u806f\u9032\u884c\u63a2\u8a0e\u3002\u521d\u6b65\u7684\u6558\u8ff0\u7d71\u8a08\u4e3b\u8981\u662f\u60f3\u4e86\u89e3\u5f9e\u5341\u5104\u4e2d\u6587\u8a9e\u6599\u5eab\u4e2d\u6240\u53d6\u5f97\u7684\u5be6\u969b\u8a9e \u6211\u5011\u4f7f\u7528 Sketch Engine \u4e2d\u7684 Collocate \u529f\u80fd\uff0c\u4e26\u5c07\u7d50\u679c\u8207\u8a5e\u7d44\u8a5e\u6027\u5167\u5bb9(part of speech) \u6599\u7d71\u8a08\u7d50\u679c\uff0c\u662f\u5426\u80fd\u8207\u6f22\u8a9e\u65b9\u4f4d\u540d\u8a5e\u7684\u7d44\u6210\u65b9\u5f0f\u6709\u76f8\u540c\u3002\u800c\u5728\u5f8c\u7e8c\u7684\u6982\u5ff5\u95dc\u806f\u5206\u6790\uff0c\u4e3b \u90fd\u5132\u5b58\u4e0b\u4f86\u3002\u800c\u904e\u6ffe\u65b9\u4f4d\u77ed\u53e5\u6642\uff0c\u672c\u7814\u7a76\u4ee5 Sketch Engine \u50b3\u56de\u8a5e\u7d44\u55ae\u4f4d(compound \u8981\u662f\u60f3\u4e86\u89e3\u6982\u5ff5\u9593\u7684\u7d44\u6210\u95dc\u4fc2\u662f\u5426\u6703\u56e0\u65b9\u4f4d\u8a5e\u7d44\u6210\u4e0d\u540c\u800c\u6709\u6240\u5f71\u97ff\u3002\u76f8\u95dc\u7684\u5167\u5bb9\u5206\u8ff0\u5982 \u6392\u5e8f\u539f\u5247\u6bcf\u884c\u4f9d\u540c\u7fa9/\u8fd1\u7fa9\u7a0b\u5ea6\u5728\u540c\u985e\u578b\u4e2d\u7531\u5de6\u81ea\u53f3\u6392\u5217\uff0c\u8a5e\u8a9e\u6240\u5c6c\u985e\u5225\u8207\u5217\u8209\u4f4d\u7f6e\u5247 segment)\u70ba\u57fa\u6e96\uff0c\u4e26\u4ee5\u6240\u641c\u5c0b\u7684\u65b9\u4f4d\u540d\u8a5e\u958b\u59cb\u5f80\u524d\uff0c\u82e5\u4e09\u500b\u8a5e\u7d44\u5167\u6709\"\u5728\"\u51fa\u73fe\uff0c\u5247\u6536\u9304 \u4e0b\u5217\u3002\u800c\u5404\u8a5e\u7d44\u7684\u6982\u5ff5\u662f\u4ee5\u540c\u7fa9\u8a5e\u8a5e\u6797\u4e4b\u4e2d\u6700\u9ad8\u968e\u5c64\u7684\u540c\u7fa9\u8a5e\u985e\u70ba\u4ee3\u8868\uff0c\u9664\u4e86\u6211\u5011\u53ef\u4ee5 \u96b1\u542b\u6709\u4f5c\u8005\u5011\u7684\u5de7\u601d\u3002\u800c\u96fb\u5b50\u5316\u7684\u540c\u7fa9\u8a5e\u6797\u64f4\u5c55\u7248\u662f\u7531\u54c8\u723e\u6ff1\u5de5\u696d\u5927\u5b78\u4fe1\u606f\u6aa2\u7d22\u7814\u7a76\u5ba4 \"\u5728\"\u81f3\u65b9\u4f4d\u540d\u8a5e\u4e4b\u9593\u7684\u6240\u6709\u8a5e\u7d44\u55ae\u4f4d\uff1b\u82e5\u4e09\u500b\u8a5e\u7d44\u5167\u6c92\u6709\"\u5728\"\uff0c\u5247\u50c5\u6536\u9304\u6700\u591a\u4e09\u500b\u8a5e\u7d44 \u4f9d\u5faa\u540c\u7fa9\u8a5e\u985e\u4ee3\u78bc\u5c0b\u627e\u6240\u5c6c\u7684\u9ad8\u968e\u5c64\u4ee3\u865f\u4e4b\u5916\uff0c\u4ea6\u53ef\u4ee5\u907f\u514d\u904e\u591a\u4e2d\u968e\u5c64\u77e5\u8b58\u6982\u5ff5\u7684\u4ea4\u932f</td></tr><tr><td colspan=\"5\">(HIT IR Lab)\u6240\u63d0\u4f9b\uff0c\u9664\u4e86\u6574\u7406\u3001\u9664\u4e86\u522a\u9664\u820a\u8a5e\u8207\u7f55\u7528\u8a5e\u5916\uff0c\u4e26\u4f9d\u65b0\u805e\u8a9e\u6599\u52a0\u5165\u5e38\u7528\u65b0 \u55ae\u4f4d\uff0c\u505a\u70ba\u65b9\u4f4d\u540d\u8a5e\u77ed\u53e5\u3002\u5728\u9019\u6a23\u904e\u6ffe\u539f\u5247\u4e0b\uff0c\u6211\u5011\u53ef\u4ee5\u78ba\u5b9a\u6240\u6536\u9304\u5230\u7684\u8a5e\u7d44\u55ae\u4f4d\u662f\u5c0f \u5f71\u97ff\uff0c\u800c\u5931\u53bb\u7126\u9ede\u3002</td></tr><tr><td colspan=\"5\">\u8a5e\u3002\u6b64\u5916\u518d\u5c0d\u539f\u59cb\u7684\u5206\u985e\u4e5f\u64f4\u5c55\u5230\u4e94\u5c64\uff0c\u5176\u4e2d\u52a0\u5165\u300c\u76f8\u7b49\u3001\u540c\u7fa9\u300d(=)\u3001 \u300c\u4e0d\u7b49\u3001\u540c\u985e\u300d (#)\u53ca\u300c\u81ea\u6211\u5c01\u9589\u3001\u7368\u7acb\u300d(@)\u7b49\u76f8\u95dc\u6db5\u7fa9\u3002 \u65bc\u7b49\u65bc\u4e09\uff0c\u4ee5\u5229\u5f8c\u7e8c\u5206\u6790\u3002 (1) \u65b9\u4f4d\u8a5e\u7684\u6558\u8ff0\u7d71\u8a08</td></tr><tr><td colspan=\"5\">\u8868 2 \u540c\u7fa9\u8a5e\u8a5e\u6797\u64f4\u5c55\u7248 \u4f8b \u6211\u5011\u4f7f\u7528\u4e86 10 \u500b\u65b9\u4f4d\u8a5e(\u4e0a/\u4e0b\u3001\u524d /\u5f8c\u3001\u88e1 /\u5916\u3001\u6771/\u897f\u3001\u5357 /\u5317)\uff0c\u53ca 5 \u500b\u4e0d\u540c\u7684\u7d44\u5408\u65b9\u5f0f(\u524d</td></tr><tr><td colspan=\"5\">\u98fe\u8a5e\uff1a\u4ee5\u3001\u4e4b\uff1b\u5f8c\u7db4\u8a5e\uff1a\u908a\u3001\u9762\u3001\u982d)\uff0c\u5230\u5341\u5104\u4e2d\u6587\u8a9e\u6599\u5eab\u4e2d\u64f7\u53d6\u65b9\u4f4d\u540d\u8a5e\u6240\u5b58\u5728\u7684\u53e5 Cb01A01= \u65b9\u5411 \u65b9\u4f4d \u65b9\u9762 \u65b9 \u5411 \u5b50\uff0c\u4e26\u900f\u904e\u524d\u8ff0\u7684\u904e\u6ffe\u539f\u5247(\u7531\u65b9\u4f4d\u8a5e\u70ba\u57fa\u6e96\uff0c\u5411\u524d\u8a08\u7b97\uff0c\u9047\"\u5728\"\u5373\u505c\uff0c\u6700\u591a\u4e09\u7d44)\uff0c\u9032 Cb02A01= \u6771\u5357\u897f\u5317 \u56db\u65b9 Cb03A01= \u4e0a \u4e0a\u9762 \u4e0a\u908a \u4e0a\u982d \u4e0a\u7aef \u9802\u7aef \u982d \u4e0a\u65b9 \u884c\u6558\u8ff0\u7d71\u8a08\u5206\u6790\uff0c\u5176\u7d50\u679c\u5982\u4e0b\u8868\uff1a</td></tr><tr><td colspan=\"3\">Dm01A01= \u653f\u5e9c \u5167\u95a3 \u95a3 \u7576\u5c40 \u671d</td><td/><td/></tr><tr><td colspan=\"4\">Dm01A05= \u671d\u5ef7 \u5bae\u5ef7 \u5edf\u5802 \u738b\u5ba4 \u671d \u5ef7 \u7687\u671d \u6e05\u5ef7 \u8868 3 \u5f9e\u5341\u5104\u4e2d\u6587\u8a9e\uf9be\u5eab\u4e2d\u64f7\u53d6\u7684\u65b9\u4f4d\u77ed\u53e5\u5206\u4f48</td><td/></tr><tr><td>\u5f8c\u7db4\u8a5e Aa01B03# \u826f\u6c11 \u9806\u6c11 Bg03A01@ \u706b ~\u908a ~\u9762</td><td>~\u982d</td><td>\u524d\u98fe\u8a5e \u4ee5 ~ \u4e4b ~</td><td>\u8a08\u6b21</td><td>\u4f54\u7e3d\u6bd4\u7387</td></tr><tr><td colspan=\"5\">\u4e0a \u5728\u8868 2 \u4e2d\u53ef\u770b\u5f97\u51fa\uff0c\u540c\u7fa9\u8a5e\u8a5e\u6797\u64f4\u5c55\u7248\u90fd\u4fdd\u7559\u4e86\u5206\u985e\u985e\u5225\u3001\u5b57\u5f59\u53ca\u540c\u7fa9\u8a5e\u5f59\uff0c\u4e14\u6c92\u6709\u91dd 11 788 51 1557 15559 17966 15% \u4e0b 6 169 3 8273 7547 15998 13% \u5c0d\u8a72\u985e\u5225\u7d66\u4e88\u660e\u78ba\u7684\u985e\u5225\u6db5\u7fa9\u5b9a\u7fa9\uff0c\u4ea6\u6c92\u6709\u5c0d\u985e\u5225\u4e2d\u7684\u8a5e\u5f59\u7d66\u4e88\u660e\u78ba\u5b9a\u7fa9\u3002\u5728\u5206\u985e\u4e4b \u524d 3 1085 154 31618 12596 45456 38% \u4e2d\uff0c\u6bcf\u884c\u6700\u524d\u9762\u7684\u82f1\u6587\u8207\u6578\u5b57\u7b26\u865f\u4ee3\u8868\u5176\u540c\u7fa9\u8a5e\u7d44\u7684\u7de8\u865f\uff0c\u4ee5 Cb01A01, Cb02A01, \u5f8c 9 1028 215 22051 3751 27054 23% Cb03A01 \u4e09\u7d44\u770b\u4f86\uff0c\u6211\u5011\u53ef\u4ee5\u5927\u9ad4\u4e0a\u5f9e\u8a9e\u7fa9\u4e86\u89e3 Cb \u4e00\u985e\u662f\u65b9\u5411\u6027\u7684\u8a5e\u5f59\uff1b\u540c\u7406\uff0c Dm01A01 \u8207 Dm01A05 \u5169\u7d44\u8a5e\u7d44\u70ba\u4e0d\u540c\u6642\u4ee3\u7684\u653f\u5e9c\u6a5f\u69cb\u540d\u8a5e\u3002\u53e6\u4e00\u500b\u540c\u7fa9\u8a5e\u8a5e\u6797\u6240\u5b58 \u88e1 9 1086 97 0 0 1192 1%</td></tr><tr><td colspan=\"5\">\u5728\u7684\u554f\u984c\u662f\uff0c\u4e00\u5b57/\u8a5e\u591a\u7fa9\u6703\u540c\u6642\u88ab\u6b78\u5165\u4e0d\u540c\u7684\u8a5e\u7d44\u4e4b\u4e2d\u3002\u4f8b\u5982\u5728 Dm01A01 \u8207 Dm01A05 \u5916 28 1254 154 4370 1918 7724 7%</td></tr><tr><td colspan=\"5\">\u88e1\uff0c\u6211\u5011\u53ef\u4ee5\u770b\u5230\"\u671d\"\u5b57\u88ab\u540c\u6642\u5217\u5728\u5169\u540c\u7fa9\u8a5e\u7d44\u88e1\u3002\u6700\u5f8c\uff0c\u540c\u7fa9\u8a5e\u8a5e\u6797\u7684\u5206\u985e\u4ee3\u78bc\u4e0a\u53ef \u6771 139 33 0 0 424 596 1%</td></tr><tr><td colspan=\"5\">\u4ee5\u770b\u51fa\uff0c\u7b2c\u4e00\u78bc\u70ba\u9ad8\u968e\u5c64\u77e5\u8b58\u6982\u5ff5\u5c64\u7d1a\uff0c\u5373\u524d\u8ff0\u7684\u5341\u4e8c\u7d44\u5927\u985e\u3002\u800c Cb(\u65b9\u5411)\u5373\u70ba\u6642\u9593/ \u5716 1 \u7814\u7a76\u6d41\u7a0b\u5716 \u897f 147 66 3 0 874 1090 1%</td></tr><tr><td colspan=\"5\">\u7a7a\u9593(C)\u7684\u4e2d\u968e\u5c64\u5b50\u985e\u5225\uff0cDm(\u6a5f\u69cb)\u5247\u70ba\u62bd\u8c61\u4e8b\u7269(D)\u7684\u77e5\u8b58\u6982\u5ff5\u4e2d\u968e\u5c64\u5b50\u985e\u5225\u3002 \u5357 118 20 0 0 390 528 0%</td></tr><tr><td colspan=\"5\">\u5728\u9032\u884c\u540c\u7fa9\u8a5e\u4ee3\u78bc\u8f49\u63db\u904e\u7a0b\u4e4b\u524d\uff0c\u56e0\u70ba\u540c\u7fa9\u8a5e\u8a5e\u6797\u70ba\u7c21\u9ad4\u5b57\u78bc\u7de8\u5beb\uff0c\u6240\u4ee5\u6211\u5011\u4f7f\u7528\u4e86\u7dad \u5317 199 78 0 0 731 1008 1% \u4e09\u3001\u7814\u7a76\u65b9\u6cd5\u8207\u7d50\u679c \u57fa\u767e\u79d1\u7684\u7e41\u7c21\u5206\u6b67\u8a5e\u8868\u9032\u884c\u7e41\u7c21\u8f49\u63db\u3002\u7dad\u57fa\u767e\u79d1\u7684\u7e41\u7c21\u5206\u6b67\u8a5e\u8868\u5305\u62ec\u4e86\u5927\u9678\u3001\u53f0\u7063\u3001\u9999 669 5607 677 67869 43790 118612</td></tr><tr><td colspan=\"5\">(\u4e00)\u8cc7\u6599\u641c\u96c6\u3001\u8655\u7406\u53ca\u5206\u6790\u65b9\u6cd5 \u6e2f\u8207\u65b0\u52a0\u5761\u5404\u5730\u7684\u6f22\u8a9e\u7de8\u78bc\u8207\u8a5e\u5f59\u4e92\u63db\u539f\u5247\uff0c\u4f8b\u5982 hardware \u4e00\u8a5e\u5728\u5927\u9678\u7a31\u4f5c\"\u786c\u4ef6\"\u3001 1% 5% 1% 57% 37%</td></tr><tr><td colspan=\"5\">\u53f0\u7063\u5247\u7a31\u505a\"\u786c\u9ad4\"\uff0c\u4f7f\u540c\u7fa9\u8a5e\u8a5e\u6797\u66f4\u5207\u5408\u53f0\u7063\u7528\u8a9e\u3002\u5728\u9032\u884c\u8f49\u63db\u904e\u7a0b\u4e2d\uff0c\u6211\u5011\u4ee5 Sketch</td></tr><tr><td colspan=\"5\">Engine \u50b3\u56de\u8a5e\u7d44\u55ae\u4f4d\u70ba\u57fa\u6e96\uff0c\u5728\u540c\u7fa9\u8a5e\u8a5e\u6797\u4e2d\u5c0b\u627e\u5b8c\u5168\u7b26\u5408\u7684\u540c\u7fa9\u8a5e\u4ee3\u78bc\u3002\u5728\u5148\u524d\u5df2\u63d0 \u6211\u5011\u5c07\u672c\u7814\u7a76\u9032\u884c\u7684\u6982\u5ff5\u6d41\u7a0b\u5716\u5448\u73fe\u5728\u6b21\u9801\u7684\u5716 1\uff0c\u8a73\u7d30\u8aaa\u660e\u5982\u4e0b\uff1a\u9996\u5148\u6211\u5011\u5148\u4f9d\u7167\u65b9 \u53ca\uff0c\u540c\u7fa9\u8a5e\u8a5e\u6797\u6703\u6709\u591a\u7fa9\u5b57\u540c\u6642\u4e26\u5206\u5217\u65bc\u4e0d\u540c\u540c\u7fa9\u8a5e\u7d44\u4e4b\u4e2d\uff0c\u800c\u9020\u6210\u4e00\u5b57\u6709\u591a\u500b\u540c\u7fa9\u8a5e \u5728\u8868 3 \u6211\u5011\u5c07\u6578\u5b57\u8f03\u5c11\u7684\u5340\u584a\u7279\u5225\u4ee5\u7c97\u7dda\u689d\u6846\u51fa\uff0c\u4e26\u6bd4\u8f03\u8868 1 \u6f22\u8a9e\u6587\u6cd5\u4e2d\u6240\u6307\u51fa\u7684\u65b9\u4f4d \u4f4d\u8a5e\u7684\u524d\u98fe/\u5f8c\u7db4\u7d44\u5408\u8868\uff0c\u5efa\u7acb\u5408\u9069\u7684\u65b9\u4f4d\u8a5e\u7d44\u5408\u641c\u5c0b\u540d\u8a5e\u7d44\u5408\uff0c\u63a5\u8457\u5230 Sketch Engine \u8a5e\u7d44\u5408\u539f\u5247\uff0c\u6211\u5011\u5f97\u5230\u4e0b\u5217\u7684\u7d50\u679c\uff1a(a) \u4f54\u6709\u6bd4\u7387\u5206\u6790\uff1a\u56e0\u70ba\u6211\u5011\u6240\u9078\u7528\u7684\u8a9e\u6599\u662f\u7528\u4f86</td></tr></table>", | |
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| "TABREF4": { | |
| "text": "Proceedings of the Twenty-Fifth Conference on Computational Linguistics and Speech Processing(ROCLING 2013)", | |
| "content": "<table/>", | |
| "html": null, | |
| "type_str": "table", | |
| "num": null | |
| } | |
| } | |
| } | |
| } |