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EMC Dutch clinical corpus contains four types of anonymized clinical documents: entries from general practitioners, specialists’ letters, radiology reports, and discharge letters. The identified UMLS terms in the corpus are annotated for negation, temporality, and experiencer properties.
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We introduce a large semi-automatically generated dataset of ~400,000 descriptive sentences about commonsense knowledge that can be true or false in which negation is present in about 2/3 of the corpus in different forms that we use to evaluate LLMs.
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