Abstract
Long distance dependency relation is one of the main challenges for the state-of-the-art transition-based dependency parsing algorithms. In this paper, we propose a method to improve the performance of transition-based parsing with long distance collocations. With these long distance collocations, our method provides an approximate global view of the entire sentence, which is a little bit similar to top-down parsing. To further improve the accuracy of decision, we extend the set of parsing actions with two more fine-grained actions based on the types of arcs. Experimental results show that our method improve the performance of parsing effectively, especially for long sentence.
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References
Cheng, Y., Asahara, M., Matsumoto, Y.: Chinese deterministic dependency analyzer: examining effects of global features and root node finder. In: Proceedings of the Fourth SIGHAN Workshop on Chinese Language Processing, pp. 17–24 (2005)
Collins, M.: Discriminative training methods for hidden markov models: theory and experiments with perceptron algorithms. In: Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (2002)
Crammer, K., Dekel, O., Keshet, J., Shalev-Shwartz, S., Singer, Y.: Online passive-aggressive algorithms. Journal of Machine Learning Research 7, 551–585 (2006)
Goldberg, Y., Elhadad, M.: An efficient algorithm for easy-first non-directional dependency parsing. In: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 742–750 (2010)
Hajič, J., Ciaramita, M., Johansson, R., Kawahara, D., Martí, M., Màrquez, L., Meyers, A., Nivre, J., Padó, S., Štěpánek, J., et al.: The CoNLL-2009 shared task: syntactic and semantic dependencies in multiple languages. In: Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task, pp. 1–18 (2009)
Manning, C., Schütze, H.: Foundations of statistical natural language processing. MIT Press (1999)
Marcus, M.P., Marcinkiewicz, M.A., Santorini, B.: Building a large annotated corpus of english: The penn treebank. Computational linguistics 19(2), 313–330 (1993)
McDonald, R., Crammer, K., Pereira, F.: Online large-margin training of dependency parsers. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pp. 91–98 (2005)
McDonald, R.T., Nivre, J.: Characterizing the errors of data-driven dependency parsing models. In: EMNLP-CoNLL, pp. 122–131 (2007)
Nivre, J.: An efficient algorithm for projective dependency parsing. In: Proceedings of the 8th International Workshop on Parsing Technologies (IWPT) (2003)
Nivre, J., Scholz, M.: Deterministic dependency parsing of english text. In: Proceedings of the 20th International Conference on Computational Linguistics, p. 64 (2004)
Ren, H., Ji, D., Wan, J., Zhang, M.: Parsing syntactic and semantic dependencies for multiple languages with a pipeline approach. In: Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task, pp. 97–102 (2009)
Shen, L., Xu, J., Weischedel, R.M.: A new string-to-dependency machine translation algorithm with a target dependency language model. In: ACL, pp. 577–585 (2008)
Yamada, H., Matsumoto, Y.: Statistical dependency analysis with support vector machines. In: Proceedings of the International Workshop on Parsing Technologies (IWPT), vol. 3 (2003)
Zhang, M., Chen, W., Duan, X., Zhang, R.: Improving graph-based dependency parsing models with dependency language models. IEEE Transactions on Audio, Speech, and Language Processing 21(11), 2313–2323 (2013)
Zhang, Y., Clark, S.: A tale of two parsers: investigating and combining graph-based and transition-based dependency parsing using beam-search. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 562–571 (2008)
Zhang, Y., Nivre, J.: Transition-based dependency parsing with rich non-local features. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, short papers, vol. 2, pp. 188–193 (2011)
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Zhu, C., Qiu, X., Huang, X. (2015). Transition-Based Dependency Parsing with Long Distance Collocations. In: Li, J., Ji, H., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2015. Lecture Notes in Computer Science(), vol 9362. Springer, Cham. https://doi.org/10.1007/978-3-319-25207-0_2
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DOI: https://doi.org/10.1007/978-3-319-25207-0_2
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