Learning to recognize features of valid textual entailments
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Modeling semantic containment and exclusion in natural language inference
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Natural logic for textual inference
RTE '07 Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing
An extended model of natural logic
IWCS-8 '09 Proceedings of the Eighth International Conference on Computational Semantics
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Previous work has presented an accurate natural logic model for natural language inference. Other work has demonstrated the effectiveness of computing presuppositions for solving natural language inference problems. We extend this work to create a system for correctly computing lexical presuppositions and their interactions within the natural logic framework. The combination allows our system to properly handle presupposition projection from the lexical to the sentential level while taking advantage of the accuracy and coverage of the natural logic system. To solve an inference problem, our system computes a sequence of edits from premise to hypothesis. For each edit the system computes an entailment relation and a presupposition entailment relation. The relations are then separately composed according to a syntactic tree and the semantic properties of its nodes. Presuppositions are projected based on the properties of their syntactic and semantic environment. The edits are then composed and the resulting entailment relations are combined with the presupposition relation to yield an answer to the inference problem.