{"url":"/dataset/ece","name":"ECE","full_name":null,"description_markdown":"The ECE dataset (Gui et al., 2016a) is collected from SINA city news and contains 2105 instances. Its document has only one emotion word and one or more emotion causes.","description_withheld":null,"homepage":"","introduced_date":"2016-11-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/event-driven-emotion-cause-extraction-with","title":"Event-Driven Emotion Cause Extraction with Corpus Construction","first_author":"Lin Gui","url":null},"license":null,"modalities":[],"tasks":[{"name":"Emotion Cause Extraction","url":"/task/emotion-cause-extraction","datasets_with_task":"/datasets/task/emotion-cause-extraction"}],"languages":[],"variants":["ECE"],"data_loaders":[],"num_papers_in_archive":38,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/emotion-cause-extraction-on-ece","task":"Emotion Cause Extraction","dataset_variant":"ECE","rows":8,"metrics":["F1"],"first_row_in_archive_order":{"model":"UECA-Prompt","paper":"/paper/ueca-prompt-universal-prompt-for-emotion","metrics":{"F1":"84.40"},"code_links":[{"title":"yajus/ueca-prompt","url":"https://github.com/yajus/ueca-prompt"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/ueca-prompt-universal-prompt-for-emotion","title":"UECA-Prompt: Universal Prompt for Emotion Cause Analysis","date":"2022-10-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/bidirectional-hierarchical-attention-networks","title":"Bidirectional Hierarchical Attention Networks based on Document-level Context for Emotion Cause Extraction","date":"2021-11-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/a-knowledge-regularized-hierarchical-approach","title":"A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis","date":"2019-11-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/rthn-a-rnn-transformer-hierarchical-network","title":"RTHN: A RNN-Transformer Hierarchical Network for Emotion Cause Extraction","date":"2019-06-04","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":0,"samples_unverified":4,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/from-independent-prediction-to-re-ordered","title":"From Independent Prediction to Re-ordered Prediction: Integrating Relative Position and Global Label Information to Emotion Cause Identification","date":"2019-06-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-question-answering-approach-to-emotion","title":"A Question Answering Approach to Emotion Cause Extraction","date":"2017-08-18","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":4,"samples_ran":0,"samples_unverified":4,"pointer_only_for_licence":4,"papers_with_no_sample_that_ran":1,"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."}