Answering Natural Language Questions via Phrasal Semantic Parsing

@inproceedings{Xu2014AnsweringNL,
  title={Answering Natural Language Questions via Phrasal Semantic Parsing},
  author={Kun Xu and Yansong Feng and Dongyan Zhao},
  booktitle={CLEF},
  year={2014}
}
We present a question answering system (Xser) over Linked Data(DBpedia), converting users’ natural language questions into structured queries. There are two challenges involved: recognizing users’ query intention and mapping the involved semantic items against a given knowledge base (KB), which will be in turn assembled into a structured query. In this paper, we propose an efficient pipeline framework to model a user’s query intention as a phrase level dependency DAG which is then instantiated… CONTINUE READING
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  • We evaluate our approach on the QALD-4 test dataset and achieve an F-measure score of 0.72, an average precision of 0.72 and an average recall of 0.71 over 50 questions.
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