Abstract
The presented paper describes a simple instance-based learning method for dependency parsing, which is based solely on the part-of-speech n-grams extracted from training data. The presented method is not dependent on any lexical features (i.e. words or lemmas) or other morphological categories so model trained on one language can be directly applied to another similar language with harmonized tagset of coarse-grained part-of-speech categories. Using the instance-based learning allows us to directly evaluate predictive power of part-of-speech patterns on evaluation data from Czech and Slovak treebanks.
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Bohnet, B.: Top accuracy and fast dependency parsing is not a contradiction. In: Proceedings of the 23rd International Conference on Computational Linguistics, pp. 89–97 (2010)
McDonald, R., Petrov, S., Hall, K.: Multi-source transfer of delexicalized dependency parsers. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 62–72 (2011)
Zeman, D., Resnik, P.: Cross-language parser adaptation between related languages. NLP for Less Privileged Languages, pp. 35–42 (2008)
Nivre, J., Hall, J., Nilsson, J.: Memory based dependency parsing. In: Proceedings of the 8th CoNLL, Boston, Massachusetts, pp. 49–56 (2004)
Nivre, J.: Non-projective dependency parsing in expected linear time. In: Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP, Suntec, Singapore, pp. 351–359 (2009)
McDonald, R., Crammer, K., Pereira, F.: Online Large-margin Training of Dependency Parsers. In: Proceedings of ACL, 91–98 (2005)
Zeman, D., Dušek, O., Mareček, D., Popel, M., Ramasamy, L., Šťěpánek, J., Žabokrtský, Z., Hajič, J.: HamleDT: Harmonized Multi-Language Dependency Treebank. In: Language Resources and Evaluation, ISSN 1574–020X, vol. 48, no. 4, Springer, Netherlands, 601–637 (2014)
Petrov, S., Das, D., McDonald, R.: A universal part-of-speech tagset. In: arXiv:1104.2086 (2011)
Täckström, O., McDonald, R., Nivre, J.: Target language adaptation of discriminative transfer parsers. In: Proceedings of NAACL, pp. 1061–1071 (2013)
Täckström, O., McDonald, R., Uszkoreit, J.: Cross-lingual word clusters for direct transfer of linguistic structure. In: Proceedings of NAACL-HLT (2012)
Butka, P., Pócs, J., Pócsova, J.: On equivalence of conceptual scaling and generalized one-sided concept lattices. Inf. Sci. 259, 57–70 (2014)
Butka, P., Pócs, J., Pócsová, J., Sarnovský, M.: Multiple data tables processing via one-sided concept lattices. Adv. Intell. Syst. Comput. 183, 89–98 (2013)
Butka, P., Pócs, J., Pócsova, J.: Distributed computation of generalized one-sided concept lattices on sparse data tables. Comput. Inf. 34(1), 77–98 (2015)
Acknowledgments
The work presented in this paper was supported by the Slovak VEGA grant 1/0493/16 and Slovak KEGA grant 025TUKE-4/2015.
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Bednár, P. (2016). Cross-Language Dependency Parsing Using Part-of-Speech Patterns. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2016. Lecture Notes in Computer Science(), vol 9924. Springer, Cham. https://doi.org/10.1007/978-3-319-45510-5_14
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DOI: https://doi.org/10.1007/978-3-319-45510-5_14
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