Information 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.
@article{arxiv.cs/0207058,
title = {Question Answering over Unstructured Data without Domain Restrictions},
author = {Jochen L. Leidner},
journal= {arXiv preprint arXiv:cs/0207058},
year = {2007}
}
Comments
8 pages, 6 figures, 5 tables. To appear in Proc. TaCoS'02, Potsdam, Germany