{"url":"/dataset/wnut-20-task-1-extracting-entities-and","name":"WNUT 2020","full_name":"WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols","description_markdown":"The training and development dataset for our task was taken from previous work on wet lab corpus (Kulkarni et al., 2018) that consists of from the 623 protocols. We excluded the eight duplicate protocols from this dataset and then re-annotated the 615 unique protocols in BRAT (Stenetorp et al., 2012).","description_withheld":null,"homepage":"http://noisy-text.github.io/2020/wlp-task.html","introduced_date":"2020-10-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/wnut-2020-task-1-overview-extracting-entities","title":"WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols","first_author":"Jeniya Tabassum","url":null},"license":null,"modalities":[],"tasks":[{"name":"Named Entity Recognition (NER)","url":"/task/named-entity-recognition-ner","datasets_with_task":"/datasets/task/named-entity-recognition-ner"},{"name":"Relation Extraction","url":"/task/relation-extraction","datasets_with_task":"/datasets/task/relation-extraction"}],"languages":[],"variants":["WNUT 2020"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/named-entity-recognition-on-wnut-20-task-1","task":"Named Entity Recognition (NER)","dataset_variant":"WNUT 2020","rows":3,"metrics":["F1","Precision","Recall"],"first_row_in_archive_order":{"model":"mgsohrab","paper":"/paper/mgsohrab-at-wnut-2020-shared-task-1-neural","metrics":{"F1":"76.60"},"code_links":[{"title":"dnanhkhoa/WNUT-2020","url":"https://github.com/dnanhkhoa/WNUT-2020"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/relation-extraction-on-wnut-20-task-1","task":"Relation Extraction","dataset_variant":"WNUT 2020","rows":1,"metrics":["F1","Precision","Recall"],"first_row_in_archive_order":{"model":"Baseline","paper":"/paper/wnut-2020-task-1-overview-extracting-entities","metrics":{"F1":"72.5","Precision":"80.1","Recall":"66.21"},"code_links":[{"title":"jeniyat/WNUT_2020_NER","url":"https://github.com/jeniyat/WNUT_2020_NER"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/domain-specific-bert-representation-for-named","title":"Domain specific BERT representation for Named Entity Recognition of lab protocol","date":"2020-12-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/mgsohrab-at-wnut-2020-shared-task-1-neural","title":"mgsohrab at WNUT 2020 Shared Task-1: Neural Exhaustive Approach for Entity and Relation Recognition Over Wet Lab Protocols","date":"2020-11-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/wnut-2020-task-1-overview-extracting-entities","title":"WNUT-2020 Task 1 Overview: Extracting Entities and Relations from Wet Lab Protocols","date":"2020-10-27","rows_on_this_dataset":2,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}