acl acl2012 acl2012-90 acl2012-90-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Oleksandr Kolomiyets ; Steven Bethard ; Marie-Francine Moens
Abstract: We propose a new approach to characterizing the timeline of a text: temporal dependency structures, where all the events of a narrative are linked via partial ordering relations like BEFORE, AFTER, OVERLAP and IDENTITY. We annotate a corpus of children’s stories with temporal dependency trees, achieving agreement (Krippendorff’s Alpha) of 0.856 on the event words, 0.822 on the links between events, and of 0.700 on the ordering relation labels. We compare two parsing models for temporal dependency structures, and show that a deterministic non-projective dependency parser outperforms a graph-based maximum spanning tree parser, achieving labeled attachment accuracy of 0.647 and labeled tree edit distance of 0.596. Our analysis of the dependency parser errors gives some insights into future research directions.
[Amig ´o et al.201 1] Enrique Amigo´, Javier Artiles, Qi Li, and Heng Ji. 2011. An evaluation framework for aggregated temporal information extraction. In SIGIR-2011 Workshop on Entity-Oriented Search. [Artiles et al.201 1] Javier Artiles, Qi Li, Taylor Cassidy, Suzanne Tamang, and Heng Ji. 2011. CUNY BLENDER TAC-KBP201 1temporal slot filling system description. In Text Analytics Conference (TAC2011). [Bethard and Martin2007] Steven Bethard and James H. Martin. 2007. CU-TMP: Temporal relation classification using syntactic and semantic features. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), pages 129–132, Prague, Czech Republic, June. ACL. [Bethard et al.2007] Steven Bethard, James H. Martin, and Sara Klingenstein. 2007. Finding temporal structure in text: Machine learning of syntactic temporal relations. International Journal of Semantic Computing (IJSC), 1(4):441–458, 12. [Bethard et al.2012] Steven Bethard, Oleksandr Kolomiyets, and Marie-Francine Moens. 2012. Annotating narrative timelines as temporal dependency structures. In Proceedings of the International Conference on Linguistic Resources and Evaluation, Istanbul, Turkey, May. ELRA. [Boguraev and Ando2005] Branimir Boguraev and Rie Kubota Ando. 2005. TimeBank-driven TimeML analysis. In Annotating, Extracting and Reasoning about Time and Events. Springer. [Bramsen et al.2006] P. Bramsen, P. Deshpande, Y.K. Lee, and R. Barzilay. 2006. Inducing temporal graphs. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pages 189– 198. ACL. [Brewer and Lichtenstein1982] William F. Brewer and Edward H. Lichtenstein. 1982. Stories are to entertain: A structural-affect theory of stories. Journal of Pragmatics, 6(5-6):473 486. [Chambers and Jurafsky2008] N. Chambers and D. Jurafsky. 2008. Jointly combining implicit constraints improves temporal ordering. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 698–706. ACL. [Cheng et al.2007] Yuchang Cheng, Masayuki Asahara, and Yuji Matsumoto. 2007. NAIST.Japan: Tempo– ral relation identification using dependency parsed tree. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), pages 245–248, Prague, Czech Republic, June. ACL. [Chu and Liu1965] Y. J. Chu and T.H. Liu. 1965. On the shortest arborescence of a directed graph. Science Sinica, pages 1396–1400. 96 [Covington2001] M.A. Covington. 2001. A fundamental algorithm for dependency parsing. In Proceedings of the 39th Annual ACM Southeast Conference, pages 95–102. [Crammer and Singer2003] K. Crammer and Y. Singer. 2003. Ultraconservative online algorithms for multiclass problems. Journal of Machine Learning Research, 3:951–991. [Crammer et al.2006] K. Crammer, O. Dekel, J. Keshet, S. Shalev-Shwartz, and Y. Singer. 2006. Online passive-aggressive algorithms. Journal of Machine Learning Research, 7:551–585. [Edmonds1967] J. Edmonds. 1967. Optimum branchings. Journal of Research of the National Bureau of Standards, pages 233–240. [Georgiadis2003] L. Georgiadis. 2003. Arborescence optimization problems solvable by Edmonds’ algorithm. Theoretical Computer Science, 301(1-3):427–437. [Gupta and Ji2009] Prashant Gupta and Heng Ji. 2009. Predicting unknown time arguments based on crossevent propagation. In Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, ACLShort ’09, pages 369–372, Stroudsburg, PA, USA. ACL. [Gusev et al.201 1] Andrey Gusev, Nathanael Chambers, Divye Raj Khilnani, Pranav Khaitan, Steven Bethard, and Dan Jurafsky. 2011. Using query patterns to learn the duration of events. In Proceedings of the International Conference on Computational Semantics, pages 145–154. [Hayes and Krippendorff2007] A.F. Hayes and K. Krippendorff. 2007. Answering the call for a standard reliability measure for coding data. Communication Methods and Measures, 1(1):77–89. [Hickmann2003] Maya Hickmann. 2003. Children ’s Discourse: Person, Space and Time Across Languages. Cambridge University Press, Cambridge, UK. [Johnson-Laird1980] P.N. Johnson-Laird. 1980. Mental models in cognitive science. Cognitive Science, 4(1):71–1 15. [Krippendorff2004] K. Krippendorff. 2004. Content analysis: An introduction to its methodology. Sage Publications, Inc. [Linguistic Data Consortium2005] Linguistic Data Consortium. 2005. ACE (Automatic Content Extraction) English annotation guidelines for events version 5.4.3 2005.07.01. [Llorens et al.2010] Hector Llorens, Estela Saquete, and Borja Navarro. 2010. TIPSem (English and Spanish): Evaluating CRFs and semantic roles in TempEval-2. In Proceedings of the 5th International Workshop on Semantic Evaluation, pages 284–291, Uppsala, Sweden, July. ACL. [McDonald et al.2005] R. McDonald, F. Pereira, K. Ribarov, and J. Hajicˇ. 2005. Non-projective dependency parsing using spanning tree algorithms. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pages 523–530. ACL. [McIntyre and Lapata2009] N. McIntyre and M. Lapata. 2009. Learning to tell tales: A data-driven approach to story generation. 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 1-Volume 1, pages 217–225. ACL. [Nivre2008] J. Nivre. 2008. Algorithms for deterministic incremental dependency parsing. Computational Linguistics, 34(4):513–553. [Pan et al.2006] Feng Pan, Rutu Mulkar, and Jerry R. Hobbs. 2006. Learning event durations from event descriptions. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, pages 393–400, Sydney, Australia, July. ACL. [Pustejovsky and Stubbs201 1] J. Pustejovsky and A. Stubbs. 2011. Increasing informativeness in temporal annotation. In Proceedings of the 5th Linguistic Annotation Workshop, pages 152–160. ACL. [Pustejovsky et al.2003a] James Pustejovsky, Jose´ Castan˜o, Robert Ingria, Roser Saury´, Robert Gaizauskas, Andrea Setzer, and Graham Katz. 2003a. TimeML: Robust specification of event and temporal expressions in text. In Proceedings of the Fifth International Workshop on Computational Semantics (IWCS-5), Tilburg. [Pustejovsky et al.2003b] James Pustejovsky, Patrick Hanks, Roser Saury´, Andrew See, Robert Gaizauskas, Andrea Setzer, Dragomir Radev, Beth Sundheim, David Day, Lisa Ferro, and Marcia Lazo. 2003b. The TimeBank corpus. In Proceedings of Corpus Linguistics, pages 647–656. [Tsarfaty et al.201 1] R. Tsarfaty, J. Nivre, and E. Andersson. 2011. Evaluating dependency parsing: Robust and heuristics-free cross-annotation evaluation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 385–396. ACL. [UzZaman and Allen2010] Naushad UzZaman and James Allen. 2010. TRIPS and TRIOS system for TempEval2: Extracting temporal information from text. In Proceedings of the 5th International Workshop on Semantic Evaluation, pages 276–283, Uppsala, Sweden, July. ACL. [Verhagen et al.2007] Marc Verhagen, Robert Gaizauskas, Frank Schilder, Graham Katz, and James Pustejovsky. 2007. SemEval2007 Task 15: TempEval temporal rela97 tion identification. In SemEval-2007: 4th International Workshop on Semantic Evaluations. [Verhagen et al.2010] Marc Verhagen, Roser Saurı´, Tommaso Caselli, and James Pustejovsky. 2010. SemEval2010 Task 13: TempEval-2. In Proceedings of the 5th International Workshop on Semantic Evaluation, SemEval ’ 10, pages 57–62, Stroudsburg, PA, USA. ACL. [Yamada and Matsumoto2003] H. Yamada and Y. Matsumoto. 2003. Statistical dependency analysis with support vector machines. In Proceedings of IWPT. [Yoshikawa et al.2009] K. Yoshikawa, S. Riedel, M. Asahara, and Y. Matsumoto. 2009. Jointly identifying temporal relations with Markov Logic. 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, pages 405–413. ACL.