Paper: Question Answering As Question-Biased Term Extraction: A New Approach Toward Multilingual QA

ACL ID P05-1027
Title Question Answering As Question-Biased Term Extraction: A New Approach Toward Multilingual QA
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005
Authors
  • Yutaka Sasaki (ATR Spoken Language Communication Research Laboratories, Kyoto Japan)

This paper regards Question Answering (QA) as Question-Biased Term Extraction (QBTE). This new QBTE approach lib- erates QA systems from the heavy bur- den imposed by question types (or answer types). In conventional approaches, a QA system analyzes a given question and de- termines the question type, and then it se- lects answers from among answer candi- dates that match the question type. Con- sequently, the output of a QA system is restricted by the design of the question types. The QBTE directly extracts an- swers as terms biased by the question. To con rm the feasibility of our QBTE ap- proach, we conducted experiments on the CRL QA Data based on 10-fold cross val- idation, using Maximum Entropy Models (MEMs) as an ML technique. Experimen- tal results showed that the trained system ac...