Strictly lexical dependency parsing

IWPT 2005 - Proceedings of the 9th International Workshop on Parsing Technologies

Volumn , Issue , 2005, Pages 152-159

  Wang, Qin Iris ^a   Schuurmans, Dale ^a   Lin, Dekang ^b  

^a UNIVERSITY OF ALBERTA   (Canada)

^b GOOGLE INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FORESTRY; NATURAL LANGUAGE PROCESSING SYSTEMS; PROBABILITY;

CONDITIONAL MODELS; CONDITIONAL PROBABILITIES; DEPENDENCY PARSING; GRAMMATICAL CATEGORY; JOINT PROBABILITY; LEXICAL DEPENDENCY; PARSE TREES; PART-OF-SPEECH TAGGER; PART-OF-SPEECH TAGS; WORD SIMILARITY;

SYNTACTICS;

EID: 80053381394     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Daniel M. Bikel. 2004. Intricacies of Collins' Parsing Model. Computational Linguistics, 30(4), pp. 479-511.
2. Daniel M. Bikel and David Chiang. 2000. Two Statistical Parsing Models applied to the Chinese Treebank. In Proceedings of the second Chinese Language Processing Workshop, pp. 1-6.
3. Eugene Charniak. 2000. A Maximum-Entropy-Inspired Parser. In Proceedings of the Second Meeting of North American Chapter of Association for Computational Linguistics (NAACL-2000), pp. 132-139.
4. Stephen Clark, Julia Hockenmaier and Mark Steedman. 2002. Building Deep Dependency Structures with a Wide-Coverage CCG Parser. In Proceedings of the 40th Annual Meeting of the ACL, pp. 327-334.
5. Michael Collins. 1996. A New Statistical Parser Based on Bigram Lexical Dependencies. In Proceedings of the 34th Annual Meeting of the ACL, pp. 184-191. Santa Cruz.
6. Michael Collins. 1997. Three Generative, Lexicalised Models for Statistical Parsing. In Proceedings of the 35th Annual Meeting of the ACL (jointly with the 8th Conference of the EACL), pp. 16-23. Madrid.
7. Michael Collins. 1999. Head-Driven Statistical Models for Natural Language Parsing. PhD Dissertation, University of Pennsylvania.
8. Ido Dagan, Lillian Lee and Fernando Pereira. 1999. Similarity-based models of cooccurrence probabilities. Machine Learning, Vol. 34(1-3) special issue on Natural Language Learning, pp. 43-69.
9. Jason M. Eisner. 1996. Three new probabilistic models for dependency parsing: An exploration. In Proceedings of COLING-96, pp. 340-345, Copenhagen.
10. Daniel Gildea. 2001. Corpus Variation and Parser Performance. In Proceedings of EMNLP-2001, pp. 167-202. Pittsburgh, PA.
11. Gregory Grefenstette. 1994. Explorations in Automatic Thesaurus Discovery. Kluwer Academic Press, Boston, MA.
12. Zelig S. Harris. 1968. Mathematical Structures of Language. Wiley, New York.
13. Donald Hindle. 1990. Noun Classification from Predicate-Argument Structures. In Proceedings of ACL-90, pp. 268-275. Pittsburg, Pennsylvania.
14. Dan Klein and Chris Manning. 2002. Fast exact inference with a factored model for natural language parsing. In Proceedings of Neural Information Processing Systems.
15. Dan Klein and Chris Manning. 2003. Accurate Unlexicalized Parsing. In Proceedings of the 41st Annual Meeting of the ACL, pp. 423-430.
16. Dan Klein and Chris Manning. 2004. Corpus-Based Induction of Syntactic Structure: Models of Dependency and Constituency. In Proceedings of the 42nd Annual Meeting of the ACL, pp. 479-486.
17. Roger Levy and Chris Manning. 2003. Is it harder to parse Chinese, or the Chinese Treebank? In Proceedings of the 41st Annual Meeting of the ACL, pp. 439-446.
18. Dekang Lin. 1995. A dependency-based method for evaluating broad-coverage parsers. In Proceedings of IJCAI-95, pp.1420-1425.
19. Dekang Lin. 1998. Automatic Retrieval and Clustering of Similar Words. In Proceeding of COLINGACL98, pp. 768-774. Montreal, Canada.
20. Ryan McDonald, Koby Crammer, and Fernando Pereira. 2005. Online large-margin training of dependency parsers. In Proceedings of ACL-2005, pp. 91-98.
21. Fernando Pereira, Naftali Z. Tishby, and Lillian Lee. 1993. Distributional clustering of English words. In Proceedings of ACL-1993, pp. 183-190, Columbus, Ohio.
22. Hiroyasu Yamada and Yuji Matsumoto. 2003. Statistical Dependency Analysis with Support Vector Machines. In Proceedings of the 8th International Workshop on Parsing Technologies, pp.195-206.