Abstract
Reasoning over several premises is not a common feature of RTE systems as it usually requires deep semantic analysis. On the other hand, FraCaS is a collection of entailment problems consisting of multiple premises and covering semantically challenging phenomena. We employ the tableau theorem prover for natural language to solve the FraCaS problems in a natural way. The expressiveness of a type theory, the transparency of natural logic and the schematic nature of tableau inference rules make it easy to model challenging semantic phenomena. The efficiency of theorem proving also becomes challenging when reasoning over several premises. After adapting to the dataset, the prover demonstrates state-of-the-art competence over certain sections of FraCaS.
Cite
CITATION STYLE
Abzianidze, L. (2016). Natural solution to fracas entailment problems. In *SEM 2016 - 5th Joint Conference on Lexical and Computational Semantics, Proceedings (pp. 64–74). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s16-2007
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