Papers › Acquisition of Phrase Correspondences using Natural Deduction Proofs

Acquisition of Phrase Correspondences using Natural Deduction Proofs

20 Apr 2018NAACL 2018 6arXiv:1804.07656archive 2025-07-28

Hitomi Yanaka, Koji Mineshima, Pascual Martinez-Gomez, Daisuke Bekki

How to identify, extract, and use phrasal knowledge is a crucial problem for the task of Recognizing Textual Entailment (RTE). To solve this problem, we propose a method for detecting paraphrases via natural deduction proofs of semantic relations between sentence pairs. Our solution relies on a graph reformulation of partial variable unifications and an algorithm that induces subgraph alignments between meaning representations. Experiments show that our method can automatically detect various paraphrases that are absent from existing paraphrase databases. In addition, the detection of paraphrases using proof information improves the accuracy of RTE tasks.

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GetTextFromScriptNode mynlp/ccg2lambda/extract_jsem_problems.py official repository unverified Apache-2.0 (permissive) · b8f1e22e03a0f287 · report
assign_ids_to_nodes mynlp/ccg2lambda/en/candc2transccg.py official repository unverified Apache-2.0 (permissive) · 3a51bbe51a2bb268 · report
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get_nodes_by_tag mynlp/ccg2lambda/en/candc2transccg.py official repository unverified Apache-2.0 (permissive) · 0c0ad808ca6abea8 · report
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