Language Challenges for Data Fusion in Question-Answering

Véronique Moriceau


Abstract
Search engines on the web and most existing question-answering systems provide the user with a set of hyperlinks and/or web page extracts containing answer(s) to a question. These answers are often incoherent to a certain degree (equivalent, contradictory, etc.). It is then quite difficult for the user to know which answer is the correct one. In this paper, we present an approach which aims at providing synthetic numerical answers in a question-answering system. These answers are generated in natural language and, in a cooperative perspective, the aim is to explain to the user the variation of numerical values when several values, apparently incoherent, are extracted from the web as possible answers to a question. We present in particular how lexical resources are essential to answer extraction from the web, to the characterization of the variation mode associated with the type of information and to answer generation in natural language.
Anthology ID:
L06-1104
Volume:
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
Month:
May
Year:
2006
Address:
Genoa, Italy
Editors:
Nicoletta Calzolari, Khalid Choukri, Aldo Gangemi, Bente Maegaard, Joseph Mariani, Jan Odijk, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/194_pdf.pdf
DOI:
Bibkey:
Cite (ACL):
Véronique Moriceau. 2006. Language Challenges for Data Fusion in Question-Answering. In Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06), Genoa, Italy. European Language Resources Association (ELRA).
Cite (Informal):
Language Challenges for Data Fusion in Question-Answering (Moriceau, LREC 2006)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2006/pdf/194_pdf.pdf