{"url":"/task/temporal-relation-classification","name":"Temporal Relation Classification","slug":"temporal-relation-classification","description_markdown":"Temporal Relation Classification is the task that is concerned with classifying the temporal relation between a pair of temporal entities (traditional events and temporal expressions). Initial approaches aimed to classify the temporal relation in thirteen relation types that were depicted by James Allen in his seminal work \"Maintaining Knowledge about Temporal Intervals\". However, due to the ambiguity in the annotation, recent corpora have been limiting the type of relations to a subset of those relations.\r\n\r\nNotice that although Temporal Relation Classification can be thought of as a subtask of Temporal Relation Extraction, the two tasks can be morphed if one adds a label that indicates the absence of a temporal relation between the entities (e.g. \"no_relation\" or \"vague\") to Temporal Relation Classification.","categories":[{"name":"Natural Language Processing","url":"/area/natural-language-processing"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":27,"papers_with_code":7,"benchmarks":4,"benchmark_tables_in_archive":4,"benchmark_tables_shown":4,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":5,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/temporal-relation-classification-on-matres","slug":"temporal-relation-classification-on-matres","dataset":"MATRES","dataset_url":"/dataset/matres","rows_in_archive":4,"metrics":["F1"],"first_row_in_archive_order":{"model":"RSGT","paper_title":"RSGT: Relational Structure Guided Temporal Relation Extraction","paper_url":"/paper/rsgt-relational-structure-guided-temporal","paper_date":"","arxiv_id":null,"code_links":[],"syntology":null}},{"leaderboard":"/sota/temporal-relation-classification-on-tb-dense","slug":"temporal-relation-classification-on-tb-dense","dataset":"TB-Dense","dataset_url":null,"rows_in_archive":3,"metrics":["F1"],"first_row_in_archive_order":{"model":"DTRE","paper_title":"DCT-Centered Temporal Relation Extraction","paper_url":"/paper/dct-centered-temporal-relation-extraction","paper_date":"","arxiv_id":null,"code_links":[],"syntology":null}},{"leaderboard":"/sota/temporal-relation-classification-on-tddauto","slug":"temporal-relation-classification-on-tddauto","dataset":"TDDAuto","dataset_url":null,"rows_in_archive":3,"metrics":["F1"],"first_row_in_archive_order":{"model":"DTRE","paper_title":"DCT-Centered Temporal Relation Extraction","paper_url":"/paper/dct-centered-temporal-relation-extraction","paper_date":"","arxiv_id":null,"code_links":[],"syntology":null}},{"leaderboard":"/sota/temporal-relation-classification-on-tddman","slug":"temporal-relation-classification-on-tddman","dataset":"TDDMan","dataset_url":null,"rows_in_archive":3,"metrics":["F1"],"first_row_in_archive_order":{"model":"DTRE","paper_title":"DCT-Centered Temporal Relation Extraction","paper_url":"/paper/dct-centered-temporal-relation-extraction","paper_date":"","arxiv_id":null,"code_links":[],"syntology":null}}],"datasets":[{"url":"/dataset/matres","name":"MATRES","full_name":"Multi-Axis Temporal RElations for Start-points","num_papers_in_archive":16},{"url":"/dataset/2012-i2b2-temporal-relations","name":"2012 i2b2 Temporal Relations","full_name":"2012 i2b2 Temporal Relations Corpus","num_papers_in_archive":9},{"url":"/dataset/french-timebank","name":"French Timebank","full_name":"","num_papers_in_archive":6},{"url":"/dataset/supplygraph","name":"SupplyGraph","full_name":"SupplyGraph: A Benchmark Dataset for Supply Chain Planning using Graph Neural Networks","num_papers_in_archive":3},{"url":"/dataset/catalan-timebank-1-0","name":"Catalan TimeBank 1.0","full_name":"","num_papers_in_archive":2}],"subtasks":[],"parent_tasks":[{"url":"/task/temporal-relation-extraction","name":"Temporal Relation Extraction"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":7,"of":7,"tagged_in_all":27,"items":[{"url":"/paper/will-llms-replace-the-encoder-only-models-in","title":"Will LLMs Replace the Encoder-Only Models in Temporal Relation Classification?","date":"2024-10-14","arxiv_id":"2410.10476","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/tieval-an-evaluation-framework-for-temporal","title":"tieval: An Evaluation Framework for Temporal Information Extraction Systems","date":"2023-01-11","arxiv_id":"2301.04643","repositories_listed":1,"syntology":null},{"url":"/paper/how-about-time-probing-a-multilingual","title":"How about Time? Probing a Multilingual Language Model for Temporal Relations","date":"2022-10-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/selecting-optimal-context-sentences-for-event","title":"Selecting Optimal Context Sentences for Event-Event Relation Extraction","date":"2022-04-02","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/utilizing-relative-event-time-to-enhance","title":"Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction","date":"2021-11-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/extracting-temporal-event-relation-with","title":"Extracting Temporal Event Relation with Syntax-guided Graph Transformer","date":"2021-04-19","arxiv_id":"2104.09570","repositories_listed":1,"syntology":null},{"url":"/paper/word-level-loss-extensions-for-neural","title":"Word-Level Loss Extensions for Neural Temporal Relation Classification","date":"2018-08-07","arxiv_id":"1808.02374","repositories_listed":1,"syntology":null}],"syntology_records":1,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}