{"url":"/dataset/agrr-2019","name":"AGRR-2019","full_name":null,"description_markdown":"Consists of 7.5k sentences with gapping (as well as 15k relevant negative sentences) and comprises data from various genres: news, fiction, social media and technical texts. The dataset was prepared for the Automatic Gapping Resolution Shared Task for Russian (AGRR-2019) - a competition aimed at stimulating the development of NLP tools and methods for processing of ellipsis. \r\n\r\nSource: [AGRR-2019: A Corpus for Gapping Resolution in Russian](/paper/agrr-2019-a-corpus-for-gapping-resolution-in)","description_withheld":null,"homepage":"https://github.com/dialogue-evaluation/AGRR-2019","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/agrr-2019-a-corpus-for-gapping-resolution-in","title":"AGRR-2019: A Corpus for Gapping Resolution in Russian","first_author":"Maria Ponomareva","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[],"variants":["AGRR-2019"],"data_loaders":[{"repo":"https://github.com/dialogue-evaluation/AGRR-2019","url":"https://github.com/dialogue-evaluation/AGRR-2019","frameworks":[]}],"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."}