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The impact of semantic class identification and semantic role labeling on natural language answer extraction
conference contribution
posted on 2008-01-01, 00:00 authored by Bahadorreza OfoghiBahadorreza Ofoghi, John YearwoodJohn Yearwood, L MaIn 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.
History
Event
British Computer Society. Conference (30th : 2008 : Glasgow, Scotland)Volume
4956Series
British Computer Society ConferencePagination
430 - 437Publisher
SpringerLocation
Glasgow, ScotlandPlace of publication
Berlin, GermanyPublisher DOI
Start date
2008-03-30End date
2008-04-03ISBN-13
978-3-540-78645-0ISBN-10
3540786457Language
engPublication classification
E1.1 Full written paper - refereed; E Conference publicationCopyright notice
2008, Springer-Verlag Berlin HeidelbergEditor/Contributor(s)
C Macdonald, I Ounis, V Plachouras, I Ruthven, R WhiteTitle of proceedings
ECIR 2008 : Proceedings of the 30th European Conference on Information RetrievalUsage metrics
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