{"url":"/dataset/dialogre","name":"DialogRE","full_name":null,"description_markdown":"**DialogRE** is the first human-annotated dialogue-based relation extraction dataset, containing 1,788 dialogues originating from the complete transcripts of a famous American television situation comedy Friends. The are annotations for all occurrences of 36 possible relation types that exist between an argument pair in a dialogue. DialogRE is available in English and Chinese.\r\n\r\nSource: [DialogRE](https://dataset.org/dialogre/)","description_withheld":null,"homepage":"https://dataset.org/dialogre/","introduced_date":"2020-04-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/dialogue-based-relation-extraction","title":"Dialogue-Based Relation Extraction","first_author":"Dian Yu","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Dialog Relation Extraction","url":"/task/dialog-relation-extraction","datasets_with_task":"/datasets/task/dialog-relation-extraction"}],"languages":[{"name":"English","url":"/datasets/language/english"},{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["DialogRE"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/dataset-org/dialog_re","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/dialog_re","frameworks":["tf","pytorch","jax"]}],"num_papers_in_archive":36,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/dialog-relation-extraction-on-dialogre","task":"Dialog Relation Extraction","dataset_variant":"DialogRE","rows":17,"metrics":["F1 (v2)","F1c (v2)","F1 (v1)","F1c (v1)","F1 (Chinese)"],"first_row_in_archive_order":{"model":"HiDialog","paper":"/paper/hierarchical-dialogue-understanding-with-1","metrics":{"F1 (v2)":"77.1","F1c (v2)":"68.2"},"code_links":[{"title":"shawx825/hidialog","url":"https://github.com/shawx825/hidialog"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/hierarchical-dialogue-understanding-with-1","title":"Hierarchical Dialogue Understanding with Special Tokens and Turn-level Attention","date":"2023-04-29","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/grasp-guiding-model-with-relational-semantics","title":"GRASP: Guiding model with RelAtional Semantics using Prompt for Dialogue Relation Extraction","date":"2022-08-26","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/global-inference-with-explicit-syntactic-and","title":"Global inference with explicit syntactic and discourse structures for dialogue-level relation extraction","date":"2022-07-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/document-level-relation-extraction-with-3","title":"Document-Level Relation Extraction with Sentences Importance Estimation and Focusing","date":"2022-04-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/d-rex-dialogue-relation-extraction-with","title":"D-REX: Dialogue Relation Extraction with Explanations","date":"2021-09-10","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/graph-based-network-with-contextualized","title":"Graph Based Network with Contextualized Representations of Turns in Dialogue","date":"2021-09-09","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":17,"samples_ran":10,"samples_unverified":7,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/socaog-incremental-graph-parsing-for-social","title":"SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues","date":"2021-06-02","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/semantic-representation-for-dialogue-modeling","title":"Semantic Representation for Dialogue Modeling","date":"2021-05-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":1,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/adaprompt-adaptive-prompt-based-finetuning","title":"KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction","date":"2021-04-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/an-embarrassingly-simple-model-for-dialogue","title":"An Embarrassingly Simple Model for Dialogue Relation Extraction","date":"2020-12-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/gdpnet-refining-latent-multi-view-graph-for","title":"GDPNet: Refining Latent Multi-View Graph for Relation Extraction","date":"2020-12-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/dialogue-relation-extraction-with-document","title":"Dialogue Relation Extraction with Document-level Heterogeneous Graph Attention Networks","date":"2020-09-10","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/dialogue-based-relation-extraction","title":"Dialogue-Based Relation Extraction","date":"2020-04-17","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":9,"samples_unverified":0,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":31,"samples_ran":20,"samples_unverified":11,"pointer_only_for_licence":5,"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."}