{"url":"/dataset/the-bioscope-corpus","name":"The BioScope Corpus","full_name":null,"description_markdown":"It is a  freely available resource for research on handling negation and uncertainty in biomedical texts . The corpus consists of three parts, namely medical free texts,biological full papers and biological scientific abstracts. The dataset contains annotations at the token level for negative and speculative keywords and at the sentence level for their linguistic scope. The annotation process was carried out by two independent linguist annotators and a chief annotator – also responsible for setting up the annotation guidelines – who resolved cases where the annotators disagreed.","description_withheld":null,"homepage":"https://rgai.inf.u-szeged.hu/node/105","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Negation Scope Resolution","url":"/task/negation-scope-resolution","datasets_with_task":"/datasets/task/negation-scope-resolution"},{"name":"Speculation Scope Resolution","url":"/task/speculation-scope-resolution","datasets_with_task":"/datasets/task/speculation-scope-resolution"},{"name":"Negation and Speculation Cue Detection","url":"/task/negation-and-speculation-cue-detection","datasets_with_task":"/datasets/task/negation-and-speculation-cue-detection"},{"name":"Negation and Speculation Scope resolution","url":"/task/negation-and-speculation-scope-resolution","datasets_with_task":"/datasets/task/negation-and-speculation-scope-resolution"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["BioScope : Abstracts","BioScope : Full Papers","The BioScope Corpus"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/negation-scope-resolution-on-bioscope","task":"Negation Scope Resolution","dataset_variant":"BioScope : Abstracts","rows":3,"metrics":["F1"],"first_row_in_archive_order":{"model":"NegBioELECTRA","paper":"/paper/no-means-no-a-non-im-proper-modeling-approach","metrics":{"F1":"98.94"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/negation-scope-resolution-on-bioscope-full","task":"Negation Scope Resolution","dataset_variant":"BioScope : Full Papers","rows":2,"metrics":["F1"],"first_row_in_archive_order":{"model":"XLNet","paper":"/paper/resolving-the-scope-of-speculation-and","metrics":{"F1":"94.4"},"code_links":[{"title":"adityak6798/Transformers-For-Negation-and-Speculation","url":"https://github.com/adityak6798/Transformers-For-Negation-and-Speculation"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/speculation-scope-resolution-on-bioscope","task":"Speculation Scope Resolution","dataset_variant":"BioScope : Abstracts","rows":2,"metrics":["F1"],"first_row_in_archive_order":{"model":"NegBioELECTRA","paper":"/paper/no-means-no-a-non-im-proper-modeling-approach","metrics":{"F1":"98.37"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/negation-and-speculation-cue-detection-on","task":"Negation and Speculation Cue Detection","dataset_variant":"BioScope : Abstracts","rows":1,"metrics":["F1"],"first_row_in_archive_order":{"model":"NegBioELECTRA","paper":"/paper/no-means-no-a-non-im-proper-modeling-approach","metrics":{"F1":"99.02"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/speculation-scope-resolution-on-bioscope-full","task":"Speculation Scope Resolution","dataset_variant":"BioScope : Full Papers","rows":1,"metrics":["F1"],"first_row_in_archive_order":{"model":"XLNet","paper":"/paper/resolving-the-scope-of-speculation-and","metrics":{"F1":"96.91"},"code_links":[{"title":"adityak6798/Transformers-For-Negation-and-Speculation","url":"https://github.com/adityak6798/Transformers-For-Negation-and-Speculation"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/no-means-no-a-non-im-proper-modeling-approach","title":"No means ‘No’; a non-im-proper modeling approach, with embedded speculative context","date":"2022-08-30","rows_on_this_dataset":3,"code_links":0,"syntology":null},{"paper":"/paper/resolving-the-scope-of-speculation-and","title":"Resolving the Scope of Speculation and Negation using Transformer-Based Architectures","date":"2020-01-09","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/negbert-a-transfer-learning-approach-for","title":"NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution","date":"2019-11-11","rows_on_this_dataset":2,"code_links":1,"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."}