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Dependency Hashing for n-best CCG Parsing

机译:N-Best CCG解析的依赖散列

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摘要

Optimising for one grammatical representation, but evaluating over a different one is a particular challenge for parsers and n-best CCG parsing. We find that this mismatch causes many n-best CCG parses to be semanti-cally equivalent, and describe a hashing technique that eliminates this problem, improving oracle n-best F-score by 0.7% and reranking accuracy by 0.4%. We also present a comprehensive analysis of errors made by the C&C CCG parser, providing the first breakdown of the impact of implementation decisions, such as supertagging, on parsing accuracy.
机译:优化一个语法表示,但在不同的一个语法表示是对解析器和N-Best CCG解析的特殊挑战。我们发现这种不匹配导致许多N-Best的CCG解析是半法地等效的,并且描述了消除此问题的散列技术,将Oracle N-Best F分数提高0.7%,重新划分为0.4%。我们还综合分析了C&C CCG解析器的错误,从而提供了实施决策的第一次破裂,例如超级标记,如解析准确性。

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