{"url":"/task/zero-shot-relation-triplet-extraction","name":"Zero-shot Relation Triplet Extraction","slug":"zero-shot-relation-triplet-extraction","description_markdown":"Given an input sentence, the task is to extract triplets consisting of the head entity, relation label, and tail entity where the relation label is not seen at the training stage.","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":5,"papers_with_code":3,"benchmarks":2,"benchmark_tables_in_archive":2,"benchmark_tables_shown":2,"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":2,"subtasks":0,"parent_tasks":1},"benchmarks":[{"leaderboard":"/sota/zero-shot-relation-triplet-extraction-on","slug":"zero-shot-relation-triplet-extraction-on","dataset":"FewRel","dataset_url":"/dataset/fewrel","rows_in_archive":3,"metrics":["Avg. F1"],"first_row_in_archive_order":{"model":"ZETT","paper_title":"Zero-shot Triplet Extraction by Template Infilling","paper_url":"/paper/zero-shot-triplet-extraction-by-template","paper_date":"2022-12-21","arxiv_id":"2212.10708","code_links":[{"title":"megagonlabs/zett","url":"https://github.com/megagonlabs/zett"}],"syntology":null}},{"leaderboard":"/sota/zero-shot-relation-triplet-extraction-on-wiki","slug":"zero-shot-relation-triplet-extraction-on-wiki","dataset":"Wiki-ZSL","dataset_url":"/dataset/wiki-zsl","rows_in_archive":2,"metrics":["Avg. F1"],"first_row_in_archive_order":{"model":"RelationPrompt","paper_title":"RelationPrompt: Leveraging Prompts to Generate Synthetic Data for Zero-Shot Relation Triplet Extraction","paper_url":"/paper/relationprompt-leveraging-prompts-to-generate","paper_date":"2022-03-17","arxiv_id":"2203.09101","code_links":[{"title":"declare-lab/relationprompt","url":"https://github.com/declare-lab/relationprompt"},{"title":"declare-lab/hyperred","url":"https://github.com/declare-lab/hyperred"}],"syntology":{"n":26,"n_ran":15,"n_unverified":11,"n_pointer_only":16}}}],"datasets":[{"url":"/dataset/fewrel","name":"FewRel","full_name":"Few-Shot Relation Classification Dataset","num_papers_in_archive":189},{"url":"/dataset/wiki-zsl","name":"Wiki-ZSL","full_name":"","num_papers_in_archive":24}],"subtasks":[],"parent_tasks":[{"url":"/task/relation-extraction","name":"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":3,"of":3,"tagged_in_all":5,"items":[{"url":"/paper/relationprompt-leveraging-prompts-to-generate","title":"RelationPrompt: Leveraging Prompts to Generate Synthetic Data for Zero-Shot Relation Triplet Extraction","date":"2022-03-17","arxiv_id":"2203.09101","repositories_listed":2,"syntology":{"n":26,"n_ran":15,"n_unverified":11,"n_pointer_only":16}},{"url":"/paper/two-are-better-than-one-joint-entity-and","title":"Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders","date":"2020-10-08","arxiv_id":"2010.03851","repositories_listed":2,"syntology":{"n":3,"n_ran":0,"n_unverified":3,"n_pointer_only":3}},{"url":"/paper/zero-shot-triplet-extraction-by-template","title":"Zero-shot Triplet Extraction by Template Infilling","date":"2022-12-21","arxiv_id":"2212.10708","repositories_listed":1,"syntology":null}],"syntology_records":2,"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"}}