{"url":"/dataset/rudas","name":"RuDaS","full_name":"Synthetic Datasets for Rule Learning","description_markdown":"Logical rules are a popular knowledge representation language in many domains. Recently, neural networks have been proposed to support the complex rule induction process. However, we argue that existing datasets and evaluation approaches are lacking in various dimensions; for example, different kinds of rules or dependencies between rules are neglected. Moreover, for the development of neural approaches, we need large amounts of data to learn from and adequate, approximate evaluation measures. In this paper, we provide a tool for generating diverse datasets and for evaluating neural rule learning systems, including novel performance metrics.","description_withheld":null,"homepage":"https://github.com/IBM/RuDaS","introduced_date":"2019-09-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/rudas-synthetic-datasets-for-rule-learning","title":"RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools","first_author":"Cristina Cornelio","url":null},"license":{"name":"Apache License 2.0","url":"https://github.com/IBM/RuDaS/blob/master/LICENSE"},"modalities":[],"tasks":[{"name":"Inductive logic programming","url":"/task/inductive-logic-programming","datasets_with_task":"/datasets/task/inductive-logic-programming"}],"languages":[],"variants":["RuDaS"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/inductive-logic-programming-on-rudas","task":"Inductive logic programming","dataset_variant":"RuDaS","rows":4,"metrics":["H-Score","R-Score"],"first_row_in_archive_order":{"model":"AMIE+","paper":"/paper/rudas-synthetic-datasets-for-rule-learning","metrics":{"H-Score":"0.2321","R-Score":"0.335"},"code_links":[{"title":"IBM/RuDaS","url":"https://github.com/IBM/RuDaS"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/rudas-synthetic-datasets-for-rule-learning","title":"RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools","date":"2019-09-16","rows_on_this_dataset":4,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"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."}