{"url":"/dataset/run","name":"RUN","full_name":"The RUN Dataset","description_markdown":"The RUN dataset  is based on OpenStreetMap (OSM). The map contains rich layers and an abundance of entities of different types. Each entity is complex and can contain (at least) four labels: name, type, is building=y/n, and house number. An entity can spread over several tiles. As the maps do not overlap, only very few entities are shared among them. The RUN dataset aligns NL navigation instructions to coordinates of their corresponding route on the OSM map.\r\n\r\nSource: [RUN](https://github.com/OnlpLab/RUN)","description_withheld":null,"homepage":"https://github.com/OnlpLab/RUN","introduced_date":"2019-09-19","introduced_date_note":null,"introduced_by":{"paper":"/paper/run-through-the-streets-a-new-dataset-and","title":"RUN through the Streets: A New Dataset and Baseline Models for Realistic Urban Navigation","first_author":"Tzuf Paz-Argaman","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Vision and Language Navigation","url":"/task/vision-and-language-navigation","datasets_with_task":"/datasets/task/vision-and-language-navigation"}],"languages":[],"variants":["RUN"],"data_loaders":[{"repo":"https://github.com/OnlpLab/RUN","url":"https://github.com/OnlpLab/RUN","frameworks":["pytorch"]}],"num_papers_in_archive":5,"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."}