Abstract
This paper presents UDRST, an unlabeled discourse parsing system in the RST framework. UDRST consists of a segmentation model and a parsing model. The segmentation model exploits subtree features to rerank N-best outputs of a base segmenter, which uses syntactic and lexical features in a CRF framework. In the parsing model, we present two algorithms for building a discourse tree from a segmented text: an incremental algorithm and a dual decomposition algorithm. Our system achieves 77.3% in the unlabeled score on the standard test set of the RST Discourse Treebank corpus, which improves 5.0% compared to HILDA [6], a state-of-the-art discourse parsing system.
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References
Bateman, J., Kleinz, J., Kamps, T., Reichenberger, K.: Towards Constructive Text, Diagram, and Layout Generation for Information Presentation. Computational Linguistics 27(3), 409–449 (2001)
Carlson, L., Marcu, D., Okurowski, M.E.: RST Discourse Treebank. Linguistic Data Consortium, LDC (2002)
Collins, M., Koo, T.: Discriminative Reranking for Natural Language Parsing. Computational Linguistics 31(1), 25–70 (2005)
Hanamoto, A., Matsuzaki, T., Tsujii, J.: Coordination Structure Analysis using Dual Decomposition. In: Proceedings of EACL, pp. 430–438 (2012)
Hernault, H., Piwek, P., Prendinger, H., Ishizuka, M.: Generating Dialogues for Virtual Agents Using Nested Textual Coherence Relations. In: Prendinger, H., Lester, J.C., Ishizuka, M. (eds.) IVA 2008. LNCS (LNAI), vol. 5208, pp. 139–145. Springer, Heidelberg (2008)
Hernault, H., Prendinger, H.A., Du Verle, D., Ishizuka, M.: HILDA: A Discourse Parser Using Support Vector Machine Classification. Dialogue and Discourse 1(3), 1–33 (2010)
Hernault, H., Bollegala, D., Ishizuka, M.: A Sequential Model for Discourse Segmentation. In: Gelbukh, A. (ed.) CICLing 2010. LNCS, vol. 6008, pp. 315–326. Springer, Heidelberg (2010)
Klein, D., Manning, C.: Accurate Unlexicalized Parsing. In: Proceedings of ACL, pp. 423–430 (2003)
Koo, T., Rush, A.M., Collins, M., Jaakkola, T., Sontag, D.: Dual Decomposition for Parsing with Non-Projective Head Automata. In: Proceedings of EMNLP, pp. 1288–1298 (2010)
Kudo, T.: CRF++: Yet Another CRF toolkit, http://crfpp.sourceforge.net/
Lafferty, J., McCallum, A., Pereira, F.: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In: Proceedings of ICML, pp. 282–289 (2001)
Louis, A., Joshi, A., Nenkova, A.: Discourse indicators for content selection in summarization. In: Proceedings of SIGDIAL, pp. 147–156 (2010)
Mann, W.C., Thompson, S.A.: Rhetorical Structure Theory. Toward a Functional Theory of Text Organization. Text 8, 243–281 (1988)
Marcu, D.: The Theory and Practice of Discourse Parsing and Summarization. MIT Press, Cambridge (2000)
Rush, A.M., Sontag, D., Collins, M., Tommi, J.: On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing. In: Proceedings of EMNLP, pp. 1–11 (2010)
Rush, A.M., Collins, M.: A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference in Natural Language Processing. Tutorial at ACL (2011)
Sagae, K.: Analysis of Discourse Structure with Syntactic Dependencies and Data-Driven Shift-Reduce Parsing. In: Proceedings of IWPT, pp. 81–84 (2009)
Soricut, R., Marcu, D.: Sentence Level Discourse Parsing using Syntactic and Lexical Information. In: Proceedings of NAACL, pp. 149–156 (2003)
Subba, R., Di Eugenio, B.: Automatic Discourse Segmentation using Neural Networks. In: Proceedings of SemDial, pp. 189–190 (2007)
Thanh, H.L., Abeysinghe, G., Huyck, C.: Generating Discourse Structures for Written Texts. In: Proceedings of COLING, pp. 329–335 (2004)
Zirn, C., Niepert, M., Stuckenschmidt, H., Strube, M.: Fine-Grained Sentiment Analysis with Structural Features. In: Proceedings of IJCNLP, pp. 336–344 (2011)
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Xuan Bach, N., Le Minh, N., Shimazu, A. (2012). UDRST: A Novel System for Unlabeled Discourse Parsing in the RST Framework. In: Isahara, H., Kanzaki, K. (eds) Advances in Natural Language Processing. JapTAL 2012. Lecture Notes in Computer Science(), vol 7614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33983-7_25
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DOI: https://doi.org/10.1007/978-3-642-33983-7_25
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