Abstract
Nominal compounds (NCs) are lexical units that consist of two or more elements that exist on their own, function as a noun and have a special added meaning. Here, we present the results of our experiments on how the growth of Wikipedia added to the performance of our dictionary labeling methods to detecting NCs. We also investigated how the size of an automatically generated silver standard corpus can affect the performance of our machine learning-based method. The results we obtained demonstrate that the bigger the dataset, the better the performance will be.
This work was supported in part by the European Union and the European Social Fund through the project FuturICT.hu (grant no.: TÁMOP-4.2.2.C-11/1/KONV-2012-0013).
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References
Sag, I.A., Baldwin, T., Bond, F., Copestake, A., Flickinger, D.: Multiword Expressions: A Pain in the Neck for NLP. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 1–15. Springer, Heidelberg (2002)
Vincze, V., Nagy T., I., Berend, G.: Multiword expressions and named entities in the Wiki50 corpus. In: Proceedings of RANLP 2011, Hissar, Bulgaria (2011)
Bonin, F., Dell’Orletta, F., Venturi, G., Montemagni, S.: Contrastive filtering of domain-specific multi-word terms from different types of corpora. In: Proceedings of the 2010 Workshop on Multiword Expressions: from Theory to Applications, pp. 77–80. Coling 2010 Organizing Committee, Beijing (2010)
de Medeiros Caseli, H., Villavicencio, A., Machado, A., Finatto, M.J.: Statistically-driven alignment-based multiword expression identification for technical domains. In: Proceedings of the Workshop on Multiword Expressions: Identification, Interpretation, Disambiguation and Applications, pp. 1–8. ACL, Singapore (2009)
Nagy T., I., Vincze, V., Berend, G.: Domain-dependent identification of multiword expressions. In: Proceedings of the International Conference on Recent Advances in Natural Language Processing 2011, pp. 622–627. RANLP 2011 Organising Committee, Hissar (2011)
Ramisch, C., Villavicencio, A., Boitet, C.: mwetoolkit: a framework for multiword expression identification. In: Proceedings of LREC 2010. ELRA, Valletta (2010)
Ramisch, C., Villavicencio, A., Boitet, C.: Web-based and combined language models: A case study on noun compound identification. In: Coling 2010: Posters, Beijing, China, pp. 1041–1049 (2010)
Nagy T., I., Berend, G., Vincze, V.: Noun compound and named entity recognition and their usability in keyphrase extraction. In: Proceedings of the International Conference on Recent Advances in Natural Language Processing 2011, pp. 162–169. RANLP 2011 Organising Committee, Hissar (2011)
Nicholson, J., Baldwin, T.: Interpreting Compound Nominalisations. In: LREC 2008 Workshop: Towards a Shared Task for Multiword Expressions (MWE 2008), Marrakech, Morocco, pp. 43–45 (2008)
Toutanova, K., Manning, C.D.: Enriching the knowledge sources used in a maximum entropy part-of-speech tagger. In: Proceedings of EMNLP 2000, pp. 63–70. ACL, Stroudsburg (2000)
McCallum, A.K.: Mallet: A machine learning for language toolkit (2002), http://mallet.cs.umass.edu
Lafferty, J.D., McCallum, A., Pereira, F.C.N.: Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: Proceedings of the Eighteenth International Conference on Machine Learning, ICML 2001, pp. 282–289. Morgan Kaufmann Publishers Inc., San Francisco (2001)
Erk, K., Strapparava, C. (eds.): Proceedings of the 5th International Workshop on Semantic Evaluation. ACL, Uppsala (2010)
Finkel, J.R., Grenager, T., Manning, C.: Incorporating non-local information into information extraction systems by gibbs sampling. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, ACL 2005, pp. 363–370. Association for Computational Linguistics, Stroudsburg (2005)
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Nagy T., I., Vincze, V. (2013). English Nominal Compound Detection with Wikipedia-Based Methods. In: Habernal, I., Matoušek, V. (eds) Text, Speech, and Dialogue. TSD 2013. Lecture Notes in Computer Science(), vol 8082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40585-3_29
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DOI: https://doi.org/10.1007/978-3-642-40585-3_29
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