Abstract
In satisfying an information need by a Question Answering (QA) system, there are text understanding approaches which can enhance the performance of final answer extraction. Exploiting the FrameNet lexical resource in this process inspires analysis of the levels of semantic representation in the automated practice where the task of semantic class and role labeling takes place. In this paper, we analyze the impact of different levels of semantic parsing on answer extraction with respect to the individual sub-tasks of frame evocation and frame element assignment.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Erk, K., Pado, S.: Shalmaneser - A toolchain for shallow semantic parsing. In: LREC 2006 (2006)
Baker, C.F., Fillmore, C.J., Lowe, J.B.: The Berkeley FrameNet project. In: International Conference on Computational Linguistics (1998)
Fillmore, C.J.: Frame semantics and the nature of language. Annals of the New York Academy of Sciences: Conference on the Origin and Development of Language and Speech 280, 20–32 (1976)
Lowe, J.B., Baker, C.F., Fillmore, C.J.: A frame-semantic approach to semantic annotation. In: SIGLEX Workshop on Tagging Text with Lexical Semantics: Why, What, and How? (1997)
Erk, K.: Frame assignment as word sense disambiguation. In: 2006 IAENG International Workshop on Computer Science, IWCS 2006, Tilburg University, Tilburg, The Netherlands (2006)
Narayanan, S., Harabagiu, S.: Question answering based on semantic structures. In: International Conference on Computational Linguistics (COLING-2004), Switzerland (2004)
Ofoghi, B., Yearwood, J., Ghosh, R.: A hybrid question answering schema using encapsulated semantics in lexical resources. In: Sattar, A., Kang, B.-h. (eds.) AI 2006. LNCS (LNAI), vol. 4304, pp. 1276–1280. Springer, Heidelberg (2006)
Hickl, A., et al.: Question answering with LCC’s CHAUCER at TREC 2006. In: 2006 Text Retrieval Conference (TREC 2006) (2006)
Sun, R.X., et al.: Using syntactic and semantic relation analysis in question answering. In: 2005 Text Retrieval Conference (TREC-2005) (2005)
Kaisser, M., Scheible, S., Webber, B.: Experiments at the University of Edinburgh for the TREC 2006 QA track. In: 2006 Text Retrieval Conference (TREC 2006) (2006)
Shen, D., Lapata, M.: Using semantic roles to improve question answering. In: 45th Annual Meeting of the Association for Computational Linguistics, Prague (2007)
Moldovan, D., et al.: The structure and performance of an open-domain question answering system. In: Conference of the Association for Computational Linguistics (ACL-2000), Hong Kong (2000)
Clarke, C., Cormack, G., Tudhope, E.: Relevance ranking for one to three term queries. In: 5th International Conference Recherche d’Information Assistee par Ordinateur, RIAO 1997 (1997)
Ofoghi, B., Yearwood, J., Ghosh, R.: A semantic approach to boost passage retrieval effectiveness for question answering. In: 29th Australian Computer Science Conference (2006)
Burchardt, A., et al.: SALTO – a versatile multi-level annotation tool. In: LREC 2006 (2006)
Ofoghi, B., Yearwood, J., Ma, L.: Two-step comprehensive open domain text annotation with frame semantics. In: Australasian Language Technology Workshop 2007, Melbourne, Australia (2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ofoghi, B., Yearwood, J., Ma, L. (2008). The Impact of Semantic Class Identification and Semantic Role Labeling on Natural Language Answer Extraction. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78646-7_40
Download citation
DOI: https://doi.org/10.1007/978-3-540-78646-7_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78645-0
Online ISBN: 978-3-540-78646-7
eBook Packages: Computer ScienceComputer Science (R0)