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An Entailment-Based Question Answering System over Semantic Web Data

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This paper reports a novel knowledge-based Question Answering (QA) method with the use of Semantic Web technologies and textual entailment recognition. Different from most of ontology-driven QA methods, this method does not perform deep question analysis to transform a natural language question into an ontology-compliant query for answer retrieval. Instead, it performs textual entailment recognition to discover the question template entailed by a user question from the whole machine-generated set and then takes the associated SPARQL query template to produce the complete query for retrieving the answers from the Semantic Web data that subscribe to the same ontology. An evaluation ...
Mentions: China Nanjing University Cultural Heritage