{"url":"/dataset/ddi","name":"DDI","full_name":null,"description_markdown":"The **DDI**Extraction 2013 task relies on the DDI corpus which contains MedLine abstracts on drug-drug interactions as well as documents describing drug-drug interactions from the DrugBank database.\r\n\r\nSource: [DDIExtraction 2013](https://www.cs.york.ac.uk/semeval-2013/task9/)\r\nImage Source: [https://www.aclweb.org/anthology/S13-2056.pdf](https://www.aclweb.org/anthology/S13-2056.pdf)","description_withheld":null,"homepage":"https://github.com/isegura/DDICorpus","introduced_date":"2013-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Semeval-2013 task 9: Extraction of drug-drug interactions from biomedical texts (ddiextraction 2013)","first_author":null,"url":"https://www.aclweb.org/anthology/S13-2056.pdf"},"license":{"name":"CC BY-NC-SA 3.0","url":"https://creativecommons.org/licenses/by-nc-sa/3.0/"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Relation Extraction","url":"/task/relation-extraction","datasets_with_task":"/datasets/task/relation-extraction"},{"name":"Drug–drug Interaction Extraction","url":"/task/drug-drug-interaction-extraction","datasets_with_task":"/datasets/task/drug-drug-interaction-extraction"},{"name":"Medical Relation Extraction","url":"/task/medical-relation-extraction","datasets_with_task":"/datasets/task/medical-relation-extraction"}],"languages":[],"variants":["DDI extraction 2013 corpus","DDI"],"data_loaders":[],"num_papers_in_archive":54,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/drug-drug-interaction-extraction-on-ddi","task":"Drug–drug Interaction Extraction","dataset_variant":"DDI extraction 2013 corpus","rows":10,"metrics":["F1","Micro F1"],"first_row_in_archive_order":{"model":"DESC+MOL+SciBERT","paper":"/paper/using-drug-descriptions-and-molecular","metrics":{"F1":"0.8408","Micro F1":"84.08"},"code_links":[{"title":"tticoin/DESC_MOL-DDIE","url":"https://github.com/tticoin/DESC_MOL-DDIE"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/relation-extraction-on-ddi","task":"Relation Extraction","dataset_variant":"DDI","rows":3,"metrics":["F1","Micro F1"],"first_row_in_archive_order":{"model":"BioLinkBERT (large)","paper":"/paper/linkbert-pretraining-language-models-with","metrics":{"F1":"83.35","Micro F1":"83.35"},"code_links":[{"title":"michiyasunaga/LinkBERT","url":"https://github.com/michiyasunaga/LinkBERT"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/medical-relation-extraction-on-ddi-extraction","task":"Medical Relation Extraction","dataset_variant":"DDI extraction 2013 corpus","rows":2,"metrics":["F1"],"first_row_in_archive_order":{"model":"BioLinkBERT (large)","paper":"/paper/linkbert-pretraining-language-models-with","metrics":{"F1":"83.35"},"code_links":[{"title":"michiyasunaga/LinkBERT","url":"https://github.com/michiyasunaga/LinkBERT"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/linkbert-pretraining-language-models-with","title":"LinkBERT: Pretraining Language Models with Document Links","date":"2022-03-29","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":0,"samples_unverified":14,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/scifive-a-text-to-text-transformer-model-for","title":"SciFive: a text-to-text transformer model for biomedical literature","date":"2021-05-28","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":0,"samples_unverified":5,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/improving-biomedical-pretrained-language","title":"Improving Biomedical Pretrained Language Models with Knowledge","date":"2021-04-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/electramed-a-new-pre-trained-language","title":"ELECTRAMed: a new pre-trained language representation model for biomedical NLP","date":"2021-04-19","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/using-drug-descriptions-and-molecular","title":"Using Drug Descriptions and Molecular Structures for Drug-Drug Interaction Extraction from Literature","date":"2020-10-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/characterbert-reconciling-elmo-and-bert-for","title":"CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters","date":"2020-10-20","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":5,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/domain-specific-language-model-pretraining","title":"Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing","date":"2020-07-31","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/transfer-learning-in-biomedical-natural","title":"Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets","date":"2019-06-13","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/biobert-a-pre-trained-biomedical-language","title":"BioBERT: a pre-trained biomedical language representation model for biomedical text mining","date":"2019-01-25","rows_on_this_dataset":1,"code_links":19,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":25,"samples_ran":4,"samples_unverified":21,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/enhancing-drug-drug-interaction-extraction","title":"Enhancing Drug-Drug Interaction Extraction from Texts by Molecular Structure Information","date":"2018-05-15","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/drug-drug-interaction-extraction-via-1","title":"Drug–drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths","date":"2017-10-25","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/a-graph-kernel-based-on-context-vectors-for","title":"A graph kernel based on context vectors for extracting drug–drug interactions","date":"2016-03-21","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/extracting-drug-drug-interactions-from","title":"Extracting drug–drug interactions from literature using a rich feature-based linear kernel approach","date":"2015-03-19","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":5,"samples_harvested":54,"samples_ran":9,"samples_unverified":45,"pointer_only_for_licence":1,"papers_with_no_sample_that_ran":3,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}