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Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs

2019-08-31IJCNLP 2019Code Available0· sign in to hype

Soumya Sharma, Bishal Santra, Abhik Jana, T. Y. S. S. Santosh, Niloy Ganguly, Pawan Goyal

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Abstract

Recently, biomedical version of embeddings obtained from language models such as BioELMo have shown state-of-the-art results for the textual inference task in the medical domain. In this paper, we explore how to incorporate structured domain knowledge, available in the form of a knowledge graph (UMLS), for the Medical NLI task. Specifically, we experiment with fusing embeddings obtained from knowledge graph with the state-of-the-art approaches for NLI task (ESIM model). We also experiment with fusing the domain-specific sentiment information for the task. Experiments conducted on MedNLI dataset clearly show that this strategy improves the baseline BioELMo architecture for the Medical NLI task.

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