Abstract
A novel set of “tree topological features” (TTFs) is investigated for improving a classifier-based unlexicalized parser. The features capture the location and shape of subtrees in the treebank. Four main categories of TTFs are proposed and compared. Experimental results showed that each of the four categories independently improved the parsing accuracy significantly over the baseline model. When combined using the ensemble technique, the best unlexicalized parser achieves 84% accuracy without any extra language resources, and matches the performance of early lexicalized parsers. Linguistically, TTFs approximate linguistic notions such as grammatical weight, branching property and structural parallelism. This is illustrated by studying how the features capture structural parallelism in processing coordinate structures.
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References
Abney, S.: Parsing by Chunks. In: Berwick, R., Abney, S., Tenny, C. (eds.) Principle-Based Parsing. Kluwer Academic, Dordrecht (1991)
Agirre, E., Baldwin, T., Martinez, D.: Improving Parsing and PP Attachment Performance with Sense Information. In: Proceedings of the 46th Annual Meeting of the Human Language Technology Conference (HLT 2008), pp. 317–325 (2008)
Black, E., Jelinek, F., Lafferty, J., Magerman, D., Mercer, R., Roukos, S.: Towards History-based Grammars: Using Richer Models for Probabilistic Parsing. In: Proceedings of the 5th DARPA Speech and Natural Language Workshop, pp. 31–37 (1992)
Chan, S., Cheung, L., Chong, M.: Tree Topological Features for Unlexicalized Parsing. In: Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010): Poster Volume, pp. 117–125 (2010)
Charniak, E.: A Maximum-Entropy-Inspired Parser. In: Proceedings of NAACL 2000, pp. 132–139 (2000)
Charniak, E., Johnson, M.: Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking. In: Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL 2005), pp. 173–180 (2005)
Chomsky, N., Miller, G.: Introduction to the Formal Analysis of Natural Languages. In: Luce, R., Bush, R., Galanter, E. (eds.) Handbook of Mathematical Psychology, vol. 2, pp. 269–321. Wiley, New York (1963)
Collins, M.: Head-driven Statistical Models for Natural Language Parsing. Ph.D. thesis, University of Pennsylvania, Philadelphia (1999)
Collins, M.: Discriminative Reranking for Natural Language Parsing. In: Machine Learning: Proceedings of the Seventeenth International Conference (ICML 2000), Stanford, California, pp. 175–182 (2000)
Collins, M.: Head-Driven Statistical Models for Natural Language Parsing. Computational Linguistics 29(4), 589–637 (2003)
Dietterich, T.G.: Ensemble Methods in Machine Learning. In: Kittler, J., Roli, F. (eds.) MCS 2000. LNCS, vol. 1857, pp. 1–15. Springer, Heidelberg (2000)
Dubey, A., Keller, F., Sturt, P.: A Probabilistic Corpus-based Model of Syntactic Parallelism. Cognition 109(3), 326–344 (2008)
Earley, J.: An Efficient Context-Free Parsing Algorithm. Comm. ACM 6(8), 94–102 (1970)
Frazier, L., Munn, A., Clifton, C.: Processing Coordinate Structures. Journal of Psycholinguistic Research 29(4), 343–370 (2000)
Freund, Y., Schapire, R.E.: A Decision-Theoretic Generalization of On-line Learning and an Application to Boosting. Journal of Computer and System Sciences 55(1), 119–139 (1997)
Gibson, E.: Linguistic Complexity: Locality of Syntactic Dependencies. Cognition 68, 1–76 (1998)
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer, Heidelberg (2001)
Kasami, T.: An Efficient Recognition and Syntax-analysis Algorithm for Context-free Languages. Scientific Report AFCRL-65-758, Air Force Cambridge Research Lab, MA (1965)
Kay, M.: Algorithm Schemata and Data Structures in Syntactic Processing. In: Readings in Natural Language Processing, pp. 35–70. Morgans Kaufmann Publishers Inc., San Francisco (1986)
Klein, D., Manning, C.: Accurate Unlexicalized Parsing. In: Proceedings of the 41st Meeting of the Association for Computational Linguistics, pp. 423–430 (2003)
Kübler, S., McDonald, R., Nivre, J.: Dependency Parsing. Morgan & Claypool Publishers (2009)
Magerman, D.: Statistical Decision-tree Models for Parsing. In: Proceedings of the 33rd Annual Meeting on Association for Computational Linguistics, pp. 276–283 (1995)
Marcus, M., Santorini, B., Marcinkiewicz, M.: Building a Large Annotated Corpus of English: the Penn Treebank. Computational Linguistics 19(2), 313–330 (1993)
Matsuzaki, T., Miyao, Y., Tsujii, J.: Probabilistic CFG with Latent Annotations. In: Proceedings of the 43rd Annual Meeting of the ACL, pp. 75–82 (2005)
Petrov, S., Klein, D.: Learning and Inference for Hierarchically Split PCFGs. In: Proceedings of the 22nd Conference on Artificial Intelligence, Nectar Track, Vancouver (2007)
Quirk, R., Greenbaum, S., Leech, G., Svartvik, J.: A Grammar of Contemporary English. Longman, London (1972)
Ramshaw, L.A., Marcus, M.P.: Text Chunking Using Transformation-based Learning. In: Proceedings of the Third Workshop on Very Large Corpora, pp. 82–94 (1995)
Ratnaparkhi, A.: Learning to Parse Natural Language with Maximum Entropy Models. Machine Learning 34, 151–175 (1999)
Rosenbach, A.: Animacy versus Weight as Determinants of Grammatical Variation in English. Language 81(3), 613–644 (2005)
Sagae, K., Lavie, A.: A Classifier-Based Parser with Linear Run-Time Complexity. In: Proceedings of the Ninth International Workshop on Parsing Technologies (IWPT), pp. 125–132 (2005)
Sang, E.: Transforming a Chunker to a Parser. In: Veenstra, J., Daelemans, W., Sima‘an, K., Zavrel, J. (eds.) Computational Linguistics in the Netherlands 2000, pp. 177–188 (2001)
Schapire, R.E., Singer, Y.: BoosTexter: A Boosting-based System for Text Categorization. Machine Learning 39, 135–168 (2000)
Stetina, J., Nagao, M.: Corpus-based PP Attachment Ambiguity Resolution with a Semantic Dictionary. In: Proceedings of the 5th Workshop on Very Large Corpora, Beijing, China, pp. 66–80 (1997)
Tsuruoka, Y., Tsujii, J.: Chunk Parsing Revisited. In: Proceedings of the 9th International Workshop on Parsing Technologies, pp. 133–140 (2005)
Wasow, T.: Remarks on Grammatical Weight. Language Variation and Change 9, 81–105 (1997)
Xiong, D., Li, S., Liu, Q., Lin, S., Qian, Y.: Parsing the Penn Chinese Treebank with Semantic Knowledge. In: Dale, R., Wong, K.-F., Su, J., Kwong, O.Y. (eds.) IJCNLP 2005. LNCS (LNAI), vol. 3651, pp. 70–81. Springer, Heidelberg (2005)
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Chan, S.W.K., Chong, M.W.C., Cheung, L.Y.L. (2011). An Analysis of Tree Topological Features in Classifier-Based Unlexicalized Parsing. In: Gelbukh, A.F. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6608. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19400-9_13
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