MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain (2021.acl-short)
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| Challenge: | a large number of crowdworker-constructed datasets have been used to conduct natural language inference (NLI) on unstructured, domainspecific texts such as patient notes, pathology reports, and scientific papers. |
| Approach: | They investigate whether MedNLI contains lexical and syntactic annotation artifacts associated with annotation process that allow hypothesis-only classifiers to achieve better-than-random performance. |
| Outcome: | The proposed model outperforms a majority-class baseline model on a physician-annotated dataset with premises extracted from clinical notes. |
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