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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| Veröffentlicht in: | 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Jg. 1; S. 63 - 66 |
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| Sprache: | Englisch |
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IEEE
01.08.2011
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| ISBN: | 9781457713736, 145771373X |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Bonnefoy, L. Bellot, P. Benoit, M. |
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| Snippet | 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... |
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| SubjectTerms | Computational modeling Engines Information filtering Information retrieval Natural language processing Ontologies Organizations Question-Answering Smoothing methods TREC Entity Web pages Web search |
| Title | The Web as a Source of Evidence for Filtering Candidate Answers to Natural Language Questions |
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