Question Answering over Unstructured Data without Domain Restrictions

dc.creatorLeidner, Jochen L.
dc.date2002-07-14
dc.date2002-07-18
dc.date.accessioned2026-07-07T03:18:41Z
dc.date.available2026-07-07T03:18:41Z
dc.descriptionInformation needs are naturally represented as questions. Automatic Natural-Language Question Answering (NLQA) has only recently become a practical task on a larger scale and without domain constraints. This paper gives a brief introduction to the field, its history and the impact of systematic evaluation competitions. It is then demonstrated that an NLQA system for English can be built and evaluated in a very short time using off-the-shelf parsers and thesauri. The system is based on Robust Minimal Recursion Semantics (RMRS) and is portable with respect to the parser used as a frontend. It applies atomic term unification supported by question classification and WordNet lookup for semantic similarity matching of parsed question representation and free text.
dc.description8 pages, 6 figures, 5 tables. To appear in Proc. TaCoS'02, Potsdam, Germany
dc.identifierhttps://arxiv.org/abs/cs/0207058
dc.identifierhttp://arxiv.org/abs/cs/0207058
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31210
dc.subjectComputation and Language
dc.subjectInformation Retrieval
dc.subjectI.2.7; H.3.1
dc.titleQuestion Answering over Unstructured Data without Domain Restrictions
dc.typetext

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