{"url":"/sota/temporal-information-extraction-on-tempeval-3","task":{"name":"Temporal Information Extraction","url":"/task/temporal-information-extraction","note":null},"dataset":{"name":"TempEval-3","url":"/dataset/tempeval-3"},"category":"Natural Language Processing","categories":["Natural Language Processing"],"category_note":null,"description":"Temporal information extraction is the identification of chunks/tokens corresponding to temporal intervals, and the extraction and determination of the temporal relations between those. The entities extracted may be temporal expressions (timexes), eventualities (events), or auxiliary signals that support the interpretation of an entity or relation. Relations may be temporal links (tlinks), describing the order of events and times, or subordinate links (slinks) describing modality and other subordinative activity, or aspectual links (alinks) around the various influences aspectuality has on event structure.\r\n\r\nThe markup scheme used for temporal information extraction is well-described in the ISO-TimeML standard, and also on [www.timeml.org](http://www.timeml.org).\r\n\r\n```\r\n\r\n\r\n\r\n\r\n\r\n\r\n PRI20001020.2000.0127 \r\n NEWS STORY \r\n 10/20/2000 20:02:07.85 \r\n\r\n\r\n The Navy has changed its account of the attack on the USS Cole in Yemen.\r\n Officials now say the ship was hit nearly two hours after it had docked.\r\n Initially the Navy said the explosion occurred while several boats were helping\r\n the ship to tie up. The change raises new questions about how the attackers\r\n were able to get past the Navy security.\r\n\r\n\r\n 10/20/2000 20:02:28.05 \r\n\r\n\r\n\r\n\r\n\r\n\r\n```\r\n\r\nTo avoid leaking knowledge about temporal structure, train, dev and test splits must be made at document level for temporal information extraction.","description_from":"task","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","rank":"the archive's row order at snapshot; not re-ranked","rows_end_at":"2025-07-28","rows_withheld_as_spam":0,"metric_values":"the archive's strings, untouched"},"metrics":["Temporal awareness"],"metric_direction":{"note":"inferred from the metric name only (the archive records no direction); null = not inferred, chart draws points only","by_metric":{"Temporal awareness":null}},"counts":{"rows":2,"rows_with_code":0,"rows_with_paper_page":2,"rows_dated":2,"rows_using_additional_data":0},"rows":[{"rank_in_archive_order":1,"model":"Ning et al.","metrics":{"Temporal awareness":"67.2"},"uses_additional_data":false,"paper_date":"2019-06-12","paper":"/paper/a-structured-learning-approach-to-temporal-1","paper_url":"https://arxiv.org/abs/1906.04943v1","paper_title":"A Structured Learning Approach to Temporal Relation Extraction","code":null,"n_code_links":0,"syntology":null},{"rank_in_archive_order":2,"model":"ClearTK","metrics":{"Temporal awareness":"30.98"},"uses_additional_data":false,"paper_date":"2013-06-01","paper":"/paper/cleartk-timeml-a-minimalist-approach-to","paper_url":"https://aclanthology.org/S13-2002","paper_title":"ClearTK-TimeML: A minimalist approach to TempEval 2013","code":null,"n_code_links":0,"syntology":null}],"since_archive":{"claim":"Results that newer papers report for their own method, placed here by Syntology. A model pointed at the cell in the paper's own table; the number was read from that cell and checked against this leaderboard's metric, dataset, split and scale; an independent check that saw this leaderboard's other rows and every other leaderboard on the same dataset accepted it. Not reviewed by the paper's authors or by the archive's editors, and not ranked against the archive rows.","extraction_file_present":true,"measurement":{"test_papers":883,"papers_with_output":881,"judged_true":108,"judged":110,"wilson95_lower":0.9361,"measured_on":"2026-09-24","frozen_commit":"0e3de0df94"},"measurement_note":"blind adjudication of accepted entries on a held-out split of archive papers, rules frozen before the test","coverage":{"sentence":"Syntology has checked 6,795 of the 9,581 papers on this site that are newer than the archive; results from the others appear after they are checked.","complete":false,"papers_newer_than_archive":9581,"papers_checked":6795,"papers_extracted_not_yet_verified":0,"boards_without_verdict":2,"papers_not_yet_extracted":2785},"order":"newest first by month (arXiv date, else the arXiv-id month), then arXiv id descending","columns":[],"entries":[]},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per row: N of M harvested code samples from that row's paper executed on a synthesized fixture; the other M-N are unverified. Not a reproduction of the row's number; not a correctness claim. n_pointer_only_licence counts samples the site points at rather than redistributes (a licence axis, independent of ran/unverified).","rows_with_graph_line":0,"rows_with_any_sample_ran":0,"distinct_papers_with_graph_line":0,"distinct_papers_with_any_sample_ran":0,"samples_over_distinct_papers":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"each paper (arXiv id) counted once, however many rows it is behind; this is the page-level figure"},"samples_row_weighted":{"n_ran":0,"n_unverified":0,"n_samples":0,"n_pointer_only_licence":0,"note":"row-weighted: a paper behind several rows is counted once per row; inflated relative to samples_over_distinct_papers by design, kept for readers summing the per-row syntology blocks"}}}