A Dataset for N-ary Relation Extraction of Drug Combinations

• URL: http://arxiv.org/abs/2205.02289v1
• Date: Wed, 4 May 2022 19:01:16 GMT
• Title: A Dataset for N-ary Relation Extraction of Drug Combinations
• Abstract summary: Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. We construct an expert-annotated dataset for extracting information about the efficacy of drug combinations from the scientific literature.
• Score: 39.281113345967995
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Combination therapies have become the standard of care for diseases such as cancer, tuberculosis, malaria and HIV. However, the combinatorial set of available multi-drug treatments creates a challenge in identifying effective combination therapies available in a situation. To assist medical professionals in identifying beneficial drug-combinations, we construct an expert-annotated dataset for extracting information about the efficacy of drug combinations from the scientific literature. Beyond its practical utility, the dataset also presents a unique NLP challenge, as the first relation extraction dataset consisting of variable-length relations. Furthermore, the relations in this dataset predominantly require language understanding beyond the sentence level, adding to the challenge of this task. We provide a promising baseline model and identify clear areas for further improvement. We release our dataset, code, and baseline models publicly to encourage the NLP community to participate in this task.

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