acl acl2012 acl2012-193 acl2012-193-reference knowledge-graph by maker-knowledge-mining
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Author: Vanessa Wei Feng ; Graeme Hirst
Abstract: In this paper, we develop an RST-style textlevel discourse parser, based on the HILDA discourse parser (Hernault et al., 2010b). We significantly improve its tree-building step by incorporating our own rich linguistic features. We also analyze the difficulty of extending traditional sentence-level discourse parsing to text-level parsing by comparing discourseparsing performance under different discourse conditions.
Jason Baldridge and Alex Lascarides. 2005. Probabilistic head-driven parsing for discourse structure. In Proceedings of the Ninth Conference on Computational Natural Language Learning, pages 96–103. Steven Bird, Ewan Klein, and Edward Loper. 2009. Natural Language Processing with Python — Analyzing Text with the Natural Language Toolkit. O’Reilly. Lynn Carlson, Daniel Marcu, and Mary Ellen Okurowski. 2001. Building a discourse-tagged corpus in the framework of Rhetorical Structure Theory. In Proceedings of Second SIGdial Workshop on Discourse and Dialogue, pages 1–10. Chih-Chung Chang and Chih-Jen Lin. 2011. LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2: 1–27. David A. duVerle and Helmut Prendinger. 2009. A novel discourse parser based on Support Vector Machine classification. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, Volume 2, ACL ’09, pages 665–673, Stroudsburg, PA, USA. Association for Computational Linguistics. Hugo Hernault, Danushka Bollegala, and Mitsuru Ishizuka. 2010a. A semi-supervised approach to improve classification of infrequent discourse relations using feature vector extension. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 399–409, Cambridge, MA, October. Association for Computational Linguistics. Hugo Hernault, Helmut Prendinger, David A. duVerle, and Mitsuru Ishizuka. 2010b. HILDA: A discourse parser using support vector machine classification. Dialogue and Discourse, 1(3): 1–33. Thorsten Joachims. 2005. A support vector method for multivariate performance measures. In International Conference on Machine Learning (ICML), pages 377– 384. Alistair Knott and Robert Dale. 1994. Using linguistic phenomena to motivate a set of coherence relations. Discourse Processes, 18(1). Huong LeThanh, Geetha Abeysinghe, and Christian Huyck. 2004. Generating discourse structures for written texts. In Proceedings of the 20th International 68 Conference on Computational Linguistics, pages 329– 335. Ziheng Lin, Min-Yen Kan, and Hwee Tou Ng. 2009. Recognizing implicit discourse relations in the Penn Discourse Treebank. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, Volume 1, EMNLP ’09, pages 343–351. Ziheng Lin, Hwee Tou Ng, and Min-Yen Kan. 2010. A PDTB-styled end-to-end discourse parser. Technical report, School of Computing, National University of Singapore. William Mann and Sandra Thompson. 1988. Rhetorical structure theory: Toward a functional theory of text organization. Text, 8(3):243–281. Daniel Marcu and Abdessamad Echihabi. 2002. An unsupervised approach to recognizing discourse relations. In Proceedings of 40th Annual Meeting of the Association for Computational Linguistics, pages 368–375, Philadelphia, Pennsylvania, USA, July. As- sociation for Computational Linguistics. Daniel Marcu. 1997. The rhetorical parsing of natural language texts. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics, pages 96–103. Rashmi Prasad, Nikhil Dinesh, Alan Lee, Eleni Miltsakaki, Livio Robaldo, Aravind Joshi, and Bonnie Webber. 2008. The Penn Discourse Treebank 2.0. In Proceedings of the 6th International Conference on Language Resources and Evaluation (LREC 2008). David Reitter. 2003. Simple signals for complex rhetorics: On rhetorical analysis with rich-feature support vector models. LDV Forum, 18(1/2):38–52. Kenji Sagae. 2009. Analysis of discourse structure with syntactic dependencies and data-driven shift-reduce parsing. In Proceedings of the 11th International Conference on Parsing Technologies, pages 81–84. Radu Soricut and Daniel Marcu. 2003. Sentence level discourse parsing using syntactic and lexical information. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, Volume 1, pages 149–156. Rajen Subba and Barbara Di Eugenio. 2009. An effective discourse parser that uses rich linguistic information. In Proceedings of Human Language Technologies: The 2009Annual Conference ofthe North American Chapter of the Association for Computational Lin- guistics, pages 566–574. Bonnie Webber. 2004. D-LTAG: Extending lexicalized TAG to discourse. Cognitive Science, 28(5):751–779.