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Modeling Semantic Containment and Exclusion in Natural Language Inference

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If you have a question about this talk, please contact Diarmuid Ó Séaghdha.

The paper for discussion this week will be:

Bill McCartney and Christopher D. Manning. Modeling Semantic Containment and Exclusion in Natural Language Inference Proceedings of COLING -08 (received the Best Paper Award at COLING )


We propose an approach to natural language inference based on a model of natural logic, which identifies valid inferences by their lexical and syntactic features, without full semantic interpretation. We greatly extend past work in natural logic, which has focused solely on semantic containment and monotonicity, to incorporate both semantic exclusion and implicativity. Our system decomposes an inference problem into a sequence of atomic edits linking premise to hypothesis; predicts a lexical entailment relation for each edit using a statistical classifier; propagates these relations upward through a syntax tree according to semantic properties of intermediate nodes; and composes the resulting entailment relations across the edit sequence. We evaluate our system on the FraCaS test suite, and achieve a 27% reduction in error from previous work. We also show that hybridizing an existing RTE system with our natural logic system yields significant gains on the RTE3 test suite.

This talk is part of the Natural Language Processing Reading Group series.

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