The Web as a Source of Evidence for Filtering Candidate Answers to Natural Language Questions

Identifying and extracting named entities from web pages has been the subject of many researches. In this paper, we propose and evaluate some new unsupervised language modeling approaches to determine the membership level of a candidate answer, a named entity, to a natural language question to a ver...

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Bibliographic Details
Main Authors: Bonnefoy, Ludovic, Bellot, Patrice, Benoit, Michel
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
Computing methodologies > Artificial intelligence > Natural language processing
Engines
Information filtering
Information retrieval
Information systems > Information retrieval
Information systems > Information storage systems
Information systems > Information systems applications
Information systems > Information systems applications > Decision support systems > Expert systems
Natural language processing
Ontologies
Organizations
Question-Answering
Smoothing methods
TREC Entity
Web pages
Web search
Online Access:Request full text
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Summary:Identifying and extracting named entities from web pages has been the subject of many researches. In this paper, we propose and evaluate some new unsupervised language modeling approaches to determine the membership level of a candidate answer, a named entity, to a natural language question to a very fine-grained conceptual class of entity. We propose to address this issue by using the Web or DBPedia hierarchy as sources of evidence. Then, this level of membership can be used to improve the ranking of candidate answers in a question-answering task. Lastly, we present the results we obtained by participating in TREC 2010 Entity track.
DOI:10.1109/WI-IAT.2011.226