{"url":"/dataset/terms-of-service","name":"Terms of Service","full_name":null,"description_markdown":"The **Terms of Service** dataset is a law dataset corresponding to the task of identifying whether contractual terms are potentially unfair. This is a binary classification task, where positive examples are potentially unfair contractual terms (clauses) from the terms of service in consumer contracts. Article 3 of the Directive 93/13 on Unfair Terms in Consumer Contracts defines an unfair contractual term as follows. A contractual term is unfair if: (1) it has not been individually negotiated; and (2) contrary to the requirement of good faith, it causes a significant imbalance in the parties rights and obligations, to the detriment of the consumer. The Terms of Service dataset consists of 9,414 examples.","description_withheld":null,"homepage":"https://arxiv.org/pdf/1805.01217v2.pdf","introduced_date":"2018-05-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/claudette-an-automated-detector-of","title":"CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service","first_author":"Marco Lippi","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Text Classification","url":"/task/text-classification","datasets_with_task":"/datasets/task/text-classification"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Terms of Service"],"data_loaders":[],"num_papers_in_archive":21,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/text-classification-on-terms-of-service","task":"Text Classification","dataset_variant":"Terms of Service","rows":3,"metrics":["F1(10-fold)"],"first_row_in_archive_order":{"model":"Custom Legal-BERT","paper":"/paper/when-does-pretraining-help-assessing-self","metrics":{"F1(10-fold)":"78.7"},"code_links":[{"title":"reglab/casehold","url":"https://github.com/reglab/casehold"},{"title":"trusthlt/privacy-legal-nlp-lm","url":"https://github.com/trusthlt/privacy-legal-nlp-lm"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/when-does-pretraining-help-assessing-self","title":"When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset","date":"2021-04-18","rows_on_this_dataset":3,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":0,"samples_unverified":9,"pointer_only_for_licence":0,"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":1,"samples_harvested":9,"samples_ran":0,"samples_unverified":9,"pointer_only_for_licence":0,"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."}