Implementing Natural Language Inference for comparatives
Keywords:comparatives, compositional semantics, theorem proving, Combinatory Categorial Grammar, Natural Language Inference
This paper presents a computational framework for Natural Language Inference (NLI) using logic-based semantic representations and theorem-proving. We focus on logical inferences with comparatives and other related constructions in English, which are known for their structural complexity and difficulty in performing efficient reasoning. Using the so-called A-not-A analysis of comparatives, we implement a fully automated system to map various comparative constructions to semantic representations in typed first-order logic via Combinatory Categorial Grammar parsers and to prove entailment relations via a theorem prover. We evaluate the system on a variety of NLI benchmarks that contain challenging inferences, in comparison with other recent logic-based systems and neural NLI models.
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Copyright (c) 2022 Izumi Haruta, Koji Mineshima, Daisuke Bekki
This work is licensed under a Creative Commons Attribution 4.0 International License.