NADA: A robust system for non-referential pronoun detection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7099 LNAI, Issue , 2011, Pages 12-23

  Bergsma, Shane ^a   Yarowsky, David ^a  

^a JOHNS HOPKINS UNIVERSITY   (United States)

Author keywords

anaphoric; anaphoricity; coreference resolution; dummy pronoun; expletive pronoun; lexical disambiguation; nominal pronoun; non anaphoric pronoun; non referential pronoun; non referential pronoun identification; pleonastic pronoun; pronoun resolution; referential

Indexed keywords

ANAPHORIC; ANAPHORICITY; COREFERENCE RESOLUTION; DUMMY PRONOUN; EXPLETIVE PRONOUN; LEXICAL DISAMBIGUATION; NOMINAL PRONOUN; NON-ANAPHORIC PRONOUN; NON-REFERENTIAL PRONOUN; PLEONASTIC PRONOUN; PRONOUN RESOLUTION; REFERENTIAL;

ARTIFICIAL INTELLIGENCE;

EID: 84455182880     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-25917-3_2     Document Type: Conference Paper

References (33)

1. Bergsma, S., Lin, D., Goebel, R.: Distributional identification of non-referential pronouns. In: ACL 2008: HLT, pp. 10-18 (2008)
2. Bergsma, S., Lin, D., Goebel, R.: Web-scale N-gram models for lexical disambiguation. In: IJCAI, pp. 1507-1512 (2009)
3. Bergsma, S., Pitler, E., Lin, D.: Creating robust supervised classifiers via web-scale N-gram data. In: ACL, pp. 865-874 (2010)
4. Boyd, A., Gegg-Harrison, W., Byron, D.: Identifying non-referential it : A machine learning approach incorporating linguistically motivated patterns. In: ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing, pp. 40-47 (2005)
5. Brants, T., Alex Franz, A.: The Google Web 1T 5-gram Corpus Version 1.1. LDC2006T13 (2006)
6. Byron, D.: Resolving pronominal reference to abstract entities. In: ACL, pp. 80-87 (2002)
7. Charniak, E., Elsner, M.: EM works for pronoun anaphora resolution. In: EACL, pp. 148-156 (2009)
8. Cherry, C., Bergsma, S.: An Expectation Maximization approach to pronoun resolution. In: CoNLL, pp. 88-95 (2005)
9. Church, K., Hart, T., Gao, J.: Compressing trigram language models with Golomb coding. In: EMNLP-CoNLL, pp. 199-207 (2007)
10. Danlos, L.: Automatic recognition of French expletive pronoun occurrences. In: IJCNLP, pp. 73-78 (2005)
11. Denis, P., Baldridge, J.: Joint determination of anaphoricity and coreference using integer programming. In: NAACL-HLT, pp. 236-243 (2007)
12. Evans, R.: Applying machine learning toward an automatic classification of it. Literary and Linguistic Computing 16(1), 45-57 (2001)
13. Fan, R.-E., Chang, K.-W., Hsieh, C.-J., Wang, X.-R., Lin, C.-J.: LIBLINEAR: A library for large linear classification. Mach. Learn. Res. 9, 1871-1874 (2008)
14. Ge, N., Hale, J., Charniak, E.: A statistical approach to anaphora resolution. In: Proceedings of the Sixth Workshop on Very Large Corpora, pp. 161-170 (1998)
15. Guthrie, D., Hepple, M.: Storing the web in memory: Space efficient language models with constant time retrieval. In: EMNLP, pp. 262-272 (2010)
16. Hammami, S.M., Sallemi, R., Belguith, L.H.: A bayesian classifier for the identification of non-referential pronouns in Arabic. In: INFOS, Special Track On Natural Language Processing and Knowledge Mining (2010)
17. Hirst, G.: Anaphora in Natural Language Understanding: A Survey. Springer, Heidelberg (1981)
18. Hobbs, J.: Resolving pronoun references. Lingua 44(311), 339-352 (1978)
19. Kehler, A., Appelt, D., Taylor, L., Simma, A.: The (non)utility of predicateargument frequencies for pronoun interpretation. In: HLT-NAACL, pp. 289-296 (2004)
20. Koehn, P.: Europarl: A parallel corpus for statistical machine translation. In: MT Summit X, pp. 79-86 (2005)
21. Lappin, S., Leass, H.J.: An algorithm for pronominal anaphora resolution. Computational Linguistics 20(4), 535-561 (1994)
22. Marcus, M.P., Santorini, B., Marcinkiewicz, M.: Building a large annotated corpus of English: The Penn Treebank. Computational Linguistics 19(2), 313-330 (1993)
23. Miltsakaki, E.: Antelogue: Pronoun resolution for text and dialogue. In: Coling 2010: Demonstrations, pp. 41-44 (2010)
24. Mitkov, R., Evans, R., Orasan, C.: A new, fully automatic version of Mitkov's knowledge-poor pronoun resolution method. In: CICLing, pp. 168-186 (2002)
25. Müller, C.: Automatic detection of nonreferential It in spoken multi-party dialog. In: EACL, pp. 49-56 (2006)
26. Ng, V., Cardie, C.: Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution. In: COLING, pp. 730-736 (2002)
27. Paice, C.D., Husk, G.D.: Towards the automatic recognition of anaphoric features in English text: the impersonal pronoun "it". Computer Speech and Language 2, 109-132 (1987)
28. Pauls, A., Klein, D.: Faster and smaller N-Gram language models. In: ACL, pp. 258-267 (2011)
29. Rello, L., Suárez, P., Mitkov, R.: A machine learning method for identifying impersonal constructions and zero pronouns in Spanish. In: Procesamiento del Lenguaje Natural, pp. 281-287 (2010)
30. Stoyanov, V., Gilbert, N., Cardie, C., Riloff, E.: Conundrums in noun phrase coreference resolution: making sense of the state-of-the-art. In: ACL-IJCNLP, pp. 656-664 (2009)
31. Webber, B.L.: Discourse deixis: reference to discourse segments. In: ACL, pp. 113-122 (1988)
32. Weischedel, R., Brunstein, A.: BBN pronoun coreference and entity type corpus. LDC2005T33 (2005)
33. Yang, X., Jian Su, J., Tan, C.L.: Improving pronoun resolution using statisticsbased semantic compatibility information. In: ACL (2005)