Abstract
This paper proposes a model of semantic labeling based on the edit distance. The dynamic programming approach stresses on a non-exact string matching technique that takes full advantage of the underlying grammatical structure of 65,000 parse trees in a Treebank. Both part-of-speech and lexical similarity serve to identify the possible semantic labels, without miring into a pure linguistic analysis. The model described has been implemented. We also analyze the tradeoffs between the part-of-speech and lexical similarity in the semantic labeling. Experimental results for recognizing various labels in 10,000 sentences are used to justify its significances.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Abney, S.: Parsing by chunks. In: Berwick, R., Abney, S., Tenny, C. (eds.) Principle-Based Parsing, Kluwer Academic, Dordrecht (1991)
Carreras, X., Màrquez, L.: Introduction to the CoNLL-2005 shared task: Semantic role labeling. In: CoNLL. Proceedings of the 9th Conference on Computational Natural Language Learning, pp. 152–164 (2005)
Chen, K.-J., Huang, C.-R., Chang, L.-P., Hsu, H.-L.: Sinica Corpus: Design Methodology for Balanced Corpora. In: PACLIC II. Proceedings of the 11th Pacific Asia Conference on Language, Information, and Computation, Seoul Korea, pp. 167–176 (1996)
Church, K.: A stochastic parts program and noun phrase parser for unrestricted text. In: Proceedings of Second Conference on Applied Natural Language Processing, Austin, Texas (1988)
CKIP. Sinica Chinese Treebank: An Introduction of Design Methodology. Academic Sinica (2004)
Fillmore, C.J.: The case for case. In: Bach, E., Harms, R.T. (eds.) Universals in Linguistic Theory, pp. 1–90. Rinehart & Winston, Holt (1968)
Haghighi, A., Toutanova, K., Manning, C.: A joint model for semantic role labeling. In: CoNLL. Proceedings of the 9th Conference on Computational Natural Language Learning (2005)
Manning, C.D., Schutze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)
Màrquez, L., Comas, P.R., Giménez, J., Català, N.: Semantic role labeling as sequential tagging. In: CoNLL. Proceedings of the 9th Conference on Computational Natural Language Learning (2005)
Pradhan, S., Hacioglu, K., Ward, W., Martin, J.H., Jurafsky, D.: Semantic role chunking combining complementary syntactic views. In: CoNLL. Proceedings of the 9th Conference on Computational Natural Language Learning (2005)
Punyakanok, V., Koomen, P., Roth, D., Yih, W.: Generalized inference with multiple semantic role labeling systems. In: CoNLL. Proceedings of the 9th Conference on Computational Natural Language Learning (2005)
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)
Surdeanu, M., Turmo, J.: Semantic role labeling using complete syntactic analysis. In: CoNLL. Proceedings of the 9th Conference on Computational Natural Language Learning (2005)
Wagner, R.A., Fischer, M.J.: The string-to-string correction problem. Journal of the Association for Computing Machinery 21(1), 168–173 (1974)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chan, S.W.K. (2007). An Edit Distance Approach to Shallow Semantic Labeling. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77226-2_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-77226-2_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77225-5
Online ISBN: 978-3-540-77226-2
eBook Packages: Computer ScienceComputer Science (R0)