Named Entity Recognition in Question Answering of Speech Data
نویسندگان
چکیده
Our contribution is centred on a study of Named Entity (NE) recognition on speech transcripts and how it impacts on the accuracy of the final question answering system. AnswerFinder was adapted to the task of question answering on speech transcripts and participated in the QAst pilot track of the CLEF competition. We have ported AFNER, the NE recogniser of AnswerFinder, to the set of answer types expected in the QAst track.
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