{"url":"/dataset/ebm-nlp","name":"EBM-NLP","full_name":null,"description_markdown":"EBM-NLP annotates PICO (Participants, Interventions, Comparisons and Outcomes) spans in clinical trial abstracts. \r\nThe corresponding PICO Extraction task aims to identify the spans in clinical trial abstracts that describe the respective PICO elements.","description_withheld":null,"homepage":"","introduced_date":"2018-06-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-corpus-with-multi-level-annotations-of","title":"A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature","first_author":"Benjamin Nye","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Participant Intervention Comparison Outcome Extraction","url":"/task/participant-intervention-comparison-outcome","datasets_with_task":"/datasets/task/participant-intervention-comparison-outcome"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["EBM-NLP"],"data_loaders":[],"num_papers_in_archive":36,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/participant-intervention-comparison-outcome","task":"Participant Intervention Comparison Outcome Extraction","dataset_variant":"EBM-NLP","rows":5,"metrics":["F1"],"first_row_in_archive_order":{"model":"VarMAE","paper":"/paper/varmae-pre-training-of-variational-masked","metrics":{"F1":"76.01"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/varmae-pre-training-of-variational-masked","title":"VarMAE: Pre-training of Variational Masked Autoencoder for Domain-adaptive Language Understanding","date":"2022-11-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"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":1,"code_links":2,"syntology":null},{"paper":"/paper/scibert-pretrained-contextualized-embeddings","title":"SciBERT: A Pretrained Language Model for Scientific Text","date":"2019-03-26","rows_on_this_dataset":2,"code_links":6,"syntology":null},{"paper":"/paper/a-corpus-with-multi-level-annotations-of","title":"A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature","date":"2018-06-11","rows_on_this_dataset":1,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"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."}