Context-dependent Semantic Parsing for Time Expressions

We present an approach for learning context-dependent semantic parsers to identify and interpret time expressions. We use a Combinatory Categorial Grammar to construct compositional meaning representations, while considering contextual cues, such as the document creation time and the tense of the governing verb, to compute the final time values. Experiments on benchmark datasets show that our approach outperforms previous stateof-the-art systems, with error reductions of 13% to 21% in end-to-end performance.

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