Question Answering System using Multiple Information Source and Open Type Answer Merge
نویسندگان
چکیده
This paper presents a multi-strategy and multisource question answering (QA) system that can use multiple strategies to both answer natural language (NL) questions and respond to keywords. We use multiple information sources including curated knowledge base, raw text, auto-generated triples, and NL processing results. We develop open semantic answer type detector for answer merging and improve previous developed single QA modules such as knowledge base based QA, information re-
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تاریخ انتشار 2015