SuMe: A Dataset Towards Summarizing Biomedical Mechanisms

Mohaddeseh Bastan, Nishant Shankar, Mihai Surdeanu, Niranjan Balasubramanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Can language models read biomedical texts and explain the biomedical mechanisms discussed? In this work we introduce a biomedical mechanism summarization task. Biomedical studies often investigate the mechanisms behind how one entity (e.g., a protein or a chemical) affects another in a biological context. The abstracts of these publications often include a focused set of sentences that present relevant supporting statements regarding such relationships, associated experimental evidence, and a concluding sentence that summarizes the mechanism underlying the relationship. We leverage this structure and create a summarization task, where the input is a collection of sentences and the main entities in an abstract, and the output includes the relationship and a sentence that summarizes the mechanism. Using a small amount of manually labeled mechanism sentences, we train a mechanism sentence classifier to filter a large biomedical abstract collection and create a summarization dataset with 22k instances. We also introduce conclusion sentence generation as a pretraining task with 611k instances. We benchmark the performance of large bio-domain language models. We find that while the pretraining task help improves performance, the best model produces acceptable mechanism outputs in only 32% of the instances, which shows the task presents significant challenges in biomedical language understanding and summarization.

Original languageEnglish (US)
Title of host publication2022 Language Resources and Evaluation Conference, LREC 2022
EditorsNicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
PublisherEuropean Language Resources Association (ELRA)
Number of pages10
ISBN (Electronic)9791095546726
StatePublished - 2022
Event13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France
Duration: Jun 20 2022Jun 25 2022

Publication series

Name2022 Language Resources and Evaluation Conference, LREC 2022


Conference13th International Conference on Language Resources and Evaluation Conference, LREC 2022


  • Biomedical NLP
  • Explanation Generation
  • Relation Extraction
  • Summarization
  • Text Generation

ASJC Scopus subject areas

  • Language and Linguistics
  • Library and Information Sciences
  • Linguistics and Language
  • Education


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