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Recently, biomedical version of embeddings obtained from language models suchas BioELMo have shown state-of-the-art results for the textual inference taskin the medical domain. In this paper, we explore how to incorporate structureddomain knowledge, available in the form of a knowledge graph (UMLS), for theMedical NLI task. Specifically, we experiment with fusing embeddings obtainedfrom knowledge graph with the state-of-the-art approaches for NLI task (ESIMmodel). We also experiment with fusing the domain-specific sentimentinformation for the task. Experiments conducted on MedNLI dataset clearly showthat this strategy improves the baseline BioELMo architecture for the MedicalNLI task.

Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs