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TREC
2001

SiteQ: Engineering High Performance QA System Using Lexico-Semantic Pattern Matching and Shallow NLP

11 years 2 months ago
SiteQ: Engineering High Performance QA System Using Lexico-Semantic Pattern Matching and Shallow NLP
s In TREC-10, we participated in the web track (only ad-hoc task) and the QA track (only main task). In the QA track, our QA system (SiteQ) has general architecture with three processing steps: question processing, passage selection and answer processing. The key technique is LSP's (Lexico-Semantic Patterns) that are composed of linguistic entries and semantic types. LSP grammars constructed from various resources are used for answer type determination and answer matching. We also adapt AAD (Abbreviation-Appositive-Definition) processing for the queries that answer type cannot be determined or expected, encyclopedia search for increasing the matching coverage between query terms and passages, and pivot detection for the distance calculation with answer candidates. We used two-level answer types consisted of 18 upper-level types and 47 lower-level types. Semantic category dictionary, WordNet, POS combined with lexicography and a stemmer were all applied to construct the LSP knowled...
Gary Geunbae Lee, Jungyun Seo, Seungwoo Lee, Hanmi
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where TREC
Authors Gary Geunbae Lee, Jungyun Seo, Seungwoo Lee, Hanmin Jung, Bong-Hyun Cho, Changki Lee, Byung-Kwan Kwak, Jeongwon Cha, Dongseok Kim, Joohui An, Harksoo Kim, Kyungsun Kim
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