Abstract
We investigate the effect of encoding additional semantic and syntactic information sources in a classification-based machine learning approach to the task of coreference resolution for Dutch. We experiment both with a memory-based learning approach and a maximum entropy modeling method.
As an alternative to using external lexical resources, such as the low-coverage Dutch EuroWordNet, we evaluate the effect of automatically generated semantic clusters as information source. We compare these clusters, which group together semantically similar nouns, to two semantic features based on EuroWordNet encoding synonym and hypernym relations between nouns.
The syntactic function of the anaphor and antecedent in the sentence can be an important clue for resolving coreferential relations. As baseline approach, we encode syntactic information as predicted by a memory-based shallow parser in a set of features. We contrast these shallow parse based features with features encoding richer syntactic information from a dependency parser. We show that using both the additional semantic information and syntactic information lead to small but significant performance improvement of our coreference resolution approach.
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References
Rich, E., LuperFoy, S.: An architecture for anaphora resolution. In: Proceedings of the Second Conference on Applied Natural Language Processing, pp. 18–24 (1988)
Mitkov, R.: Robust pronoun resolution with limited knowledge. In: Proceedings of the 17th International Conference on Computational Linguistics (COLING-1998/ACL-1998), pp. 869–875 (1998)
McCarthy, J.: A Trainable Approach to Coreference Resolution for Information Extraction. PhD thesis, Department of Computer Science, University of Massachusetts, Amherst MA (1996)
Soon, W., Ng, H., Lim, D.: A machine learning approach to coreference resolution of noun phrases. Computational Linguistics 27(4), 521–544 (2001)
Ng, V., Cardie, C.: Combining sample selection and error-driven pruning for machine learning of coreference rules. In: Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-2002), pp. 55–62 (2002)
Culotta, A., et al.: First-order probabilistic models for coreference resolution. In: Proceedings of HLT/NAACL, pp. 81–88 (2007)
Van de Cruys, T.: Semantic clustering in dutch. In: Proceedings of the Sixteenth Computational Linguistics in the Netherlands (CLIN), pp. 17–32 (2005)
Vossen, P. (ed.): EuroWordNet: a multilingual database with lexical semantic networks. Kluwer Academic Publishers, Norwell (1998)
Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)
Poesio, M., et al.: Learning to resolve bridging references. In: Proceedings of the 42nd Meeting of the Association for Computational Linguistics (ACL 2004), pp. 143–150 (2004)
Harabagiu, S., Bunescu, R., Maiorano, S.: Text and knowledge mining for coreference resolution. In: Proceedings of the 2nd Meeting of the North American Chapter of the Association of Computational Linguistics (NAACL-2001), pp. 55–62 (2001)
Markert, K., Nissim, M.: Comparing knowledge sources for nominal anaphora resolution. Computational Linguistics 31(3), 367–401 (2005)
Ponzetto, S.P., Strube, M.: Exploiting semantic role labeling, wordnet and wikipedia for coreference resolution. In: Proceedings of the Human Language Technology Conference of the NAACL, Main Conference, pp. 192–199 (2006)
Ng, V., Cardie, C.: Improving machine learning approaches to coreference resolution. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL-2002), pp. 104–111 (2002)
Ji, H., Westbrook, D., Grishman, R.: Using semantic relations to refine coreference decisions. In: Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pp. 17–24 (2005)
Ng, V.: Semantic class induction and coreference resolution. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, Association for Computational Linguistics, pp. 536–543 (2007)
Ng, V.: Shallow semantics for coreference resolution. In: Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI-2007), pp. 1689–1694 (2007)
Lin, D.: Automatic retrieval and clustering of similar words. In: COLING-ACL, pp. 768–774 (1998)
Yang, X., Su, J.: Coreference resolution using semantic relatedness information from automatically discovered patterns. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 528–535 (2007)
Luo, X., Zitouni, I.: Multi-lingual coreference resolution with syntactic features. In: Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pp. 660–667 (2005)
Kehler, A., et al.: The (non)utility of predicate-argument frequencies for pronoun interpretation. In: Proceedings of HLT-NAACL, pp. 289–296 (2004)
Yang, X., Su, J., Tan, C.L.: Kernel-based pronoun resolution with structured syntactic knowledge. In: Proceedings of the 21st International Conference on Computational Linguistics, pp. 41–48 (2006)
Tjong Kim Sang, E.: Memory-based named entity recognition. In: Proceedings of CoNLL-2002, Taipei, Taiwan, pp. 203–206 (2002)
Daelemans, W., et al.: Memory based tagger, version 2.0, reference guide. Technical Report ILK Technical Report - ILK 03-13, Tilburg University (2003)
Tjong Kim Sang, E., Daelemans, W., Höthker, A.: Reduction of dutch sentences for automatic subtitling. In: Computational Linguistics in the Netherlands 2003, Selected Papers from the Fourteenth CLIN Meeting, pp. 109–123 (2004)
Bouma, G., van Noord, G., Malouf, R.: Alpino: Wide-coverage computational analysis of dutch. In: Computational Linguistics in The Netherlands 2000 (2001)
Hoste, V., de Pauw, G.: Knack-2002: a richly annotated corpus of dutch written text. In: The fifth international conference on Language Resources and Evaluation (LREC) (2006)
Cover, T.M., Hart, P.E.: Nearest neighbor pattern classification. Institute of Electrical and Electronics Engineers Transactions on Information Theory 13, 21–27 (1967)
Berger, A., Della Pietra, S., Della Pietra, V.: Maximum Entropy Approach to Natural Language Processing. Computational linguistics 22(1) (1996)
Daelemans, W., et al.: TiMBL: Tilburg Memory Based Learner, version 5.1, reference manual. Technical Report ILK-0402, ILK, Tilburg University (2004)
Le, Z.: Maximum Entropy Modeling Toolkit for Python and C++. Natural Language Processing Lab, Northeastern University, China (2004)
Daelemans, W., et al.: Combined optimization of feature selection and algorithm parameter interaction in machine learning of language. In: Proceedings of the 14th European Conference on Machine Learning (ECML-2003), pp. 84–95 (2003)
Vilain, M., et al.: A model-theoretic coreference scoring scheme. In: Proceedings of the Sixth Message Understanding Conference (MUC-6), pp. 45–52 (1995)
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Hendrickx, I., Hoste, V., Daelemans, W. (2008). Semantic and Syntactic Features for Dutch Coreference Resolution. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2008. Lecture Notes in Computer Science, vol 4919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78135-6_30
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DOI: https://doi.org/10.1007/978-3-540-78135-6_30
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