Abstract
In this paper we introduce a novel approach to identifying semantic frames from semantically unlabelled text corpora. There are many frame formalisms but most of them suffer from the problem that all frames must be created manually and the set of semantic roles must be predefined. The LDA-Frames approach, based on the Latent Dirichlet Allocation, avoids both these problems by employing statistics on a syntactically tagged corpus. The only information that must be given is a number of semantic frames and a number of semantic roles to be identified. The power of LDA-Frames is first shown on a small sample corpus and then on the British National Corpus.
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References
Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet Allocation. J. Mach. Learn. Res 3, 993–1022 (2003)
Fillmore, C.J.: The Case for Case. In: Universals in Linguistic Theory, Holt, Rinehart and Winston, New York (1968)
Fillmore, C.J.: Frame Semantics. In: Linguistics in the Morning Calm, pp. 111–137. Hanshin Publishing Co., Seoul (1982)
Gildea, D., Gildea, D.: Automatic Labeling of Semantic Roles. Computational Linguistic 28(3), 245–288 (2002)
Griffiths, T.L., Steyvers, M.: Finding Scientific Topics. In: Proceedings of the National Academy of Sciences of the United States of America, pp. 5228–5235 (2004)
Hanks, P., Pustejovsky, J.: A Pattern Dictionary for Natural Language Processing. In: Revue Francaise de Langue Appliquée, Brandeis University (2005)
Kilgarriff, A., Rychlý, P., Smrž, P., Tugwell, D.: The Sketch Engine. In: Proceedings of the Eleventh EURALEX International Congress, Lorient, France, pp. 205–116 (2004)
Resnik, P.: Selectional Constraints: an Information-Theoretic Model and Its Computational Realization. Cognition 61, 127–159 (1996)
Ritter, A., Mausam, Etzioni, O.: A Latent Dirichlet Allocation Method for Selectional Preferences. In: Proceedings of the 48th Annual Meeting of the ACL, pp. 424–434. Association for Computational Linguistics (2010)
Rooth, M., Riezler, S., Prescher, D., Carroll, G., Beil, F.: Inducing a Semantically Annotated Lexicon via EM-based Clustering. In: Proceedings of the 37th Annual Meeting of the ACL, pp. 104–111. Association for Computational Linguistics (1999)
Ruppenhofer, J., Ellsworth, M., Petruck, M.R.L., Johnson, C.R., Scheffczyk, J.: FrameNet II: Extended Theory and Practice (2006), http://www.icsi.berkeley.edu/framenet
Séaghdha, D.Ó.: Latent Variable Models of Selectional Preference. In: Proceedings of the 48th Annual Meeting of the ACL, pp. 435–444. Association for Computational Linguistics (2010)
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Materna, J. (2012). LDA-Frames: An Unsupervised Approach to Generating Semantic Frames. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_31
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DOI: https://doi.org/10.1007/978-3-642-28604-9_31
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