We present an approach to training a joint syntactic and semantic parser that combines syntactic training information from CCGbank with semantic training information from a knowledge base via distant supervision. The trained parser produces a full syntactic parse of any sentence, while simultaneously producing logical forms for portions of the sentence that have a semantic representation within the parser’s predicate vocabulary. We demonstrate our approach by training a parser whose semantic representation contains 130 predicates from the NELL ontology. A semantic evaluation demonstrates that this parser produces logical forms better than both comparable prior work and a pipelined syntax-then-semantics approach. A syntactic evaluation on CCGbank demonstrates that the parser’s dependency Fscore is within 2.5% of state-of-the-art.
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Krishnamurthy et al. (2014) studied this question.
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