{"url":"/dataset/labeled-data-for-citation-field-extraction","name":"Labeled data for citation field extraction","full_name":null,"description_markdown":"Citations are an important part of scientific papers, and the proper handling of them is indispensable for the science of science. Citation field extraction is the task of parsing citations: given a citation string, extract authors, title, venue, doi etc. Since the number of citations is counted by hundreds millions, efficient computer based methods for this task are very important.\r\n\r\nThe development of machine learning methods for citation field extraction requires ground truth: a large corpus of labeled citations. This dataset provides a very large (41M) corpus of labeled data obtained by the reverse process: we took structured citation lists and used BibTeX to generate labeled citation strings.","description_withheld":null,"homepage":"https://datadryad.org/stash/dataset/doi:10.5061/dryad.j0zpc86gj","introduced_date":"2021-03-21","introduced_date_note":null,"introduced_by":null,"license":{"name":"CC0","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["Labeled data for citation field extraction"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}