Question Answering over Unstructured Data without Domain Restrictions
<|reference_start|>Question Answering over Unstructured Data without Domain Restrictions: 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.<|reference_end|>
@article{leidner2002question,
    title={Question Answering over Unstructured Data without Domain Restrictions},
    author={Jochen L. Leidner},
    journal={arXiv preprint arXiv:cs/0207058},
    year={2002},
    archivePrefix={arXiv},
    eprint={cs/0207058},
    primaryClass={cs.CL cs.IR}
}