[2L5-GS-3] Knowledge utilization and sharing

[2L5-GS-3-05] Logical Reasoning Between Clinical Texts Using Axiom Injection of Disease Knowledge

〇Natsuki Murakami¹, Mana Ishida¹, Yuta Takahashi¹, Hitomi Yanaka², Daisuke Bekki¹ (1. Ochanomizu University, 2. Tokyo University)

Keywords:Recognizing Textual Entailment, Named Entity Recognition

Electronic texts in the medical field are used for research in natural language processing, including the study of Recognizing Textual Entailment in clinical texts using the compositional semantics system, ccg2lambda. One problem with existing systems is that they are unable to correctly determine implication relationships when input sentences contain medical domain-specific paraphrases, such as names of diseases. To solve this problem, a method is proposed that uses a named entity extractor for disease names and a disease dictionary to identify candidate paraphrase expressions lacking in theorem proving, and completes equivalence relations of disease names as axioms to the theorem prover. In this study, for the aforementioned method, we extend the module for deriving axioms. We also construct an inference test set that requires axiom injection of disease names and evaluate the inference system using the extended module.