{"url":"/dataset/geoglue","name":"GeoGLUE","full_name":"GeoGraphic Language Understanding Evaluation Benchmark","description_markdown":"**GeoGLUE** is a GeoGraphic Language Understanding Evaluation benchmark, which consists of six geographic text-related tasks, including geographic textual similarity on recall, geotagged geographic elements tagging, geographic composition analysis, geographic where what cut, and geographic entity alignment. All tasks' datasets are collected from open-released resources.\r\n\r\nSource: [GeoGLUE: A GeoGraphic Language Understanding Evaluation Benchmark](https://arxiv.org/pdf/2305.06545v1.pdf)\r\n\r\nImage Source: [GeoGLUE: A GeoGraphic Language Understanding Evaluation Benchmark](https://arxiv.org/pdf/2305.06545v1.pdf)","description_withheld":null,"homepage":"https://modelscope.cn/datasets/damo/GeoGLUE/summary","introduced_date":"2023-05-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/geoglue-a-geographic-language-understanding","title":"GeoGLUE: A GeoGraphic Language Understanding Evaluation Benchmark","first_author":"Dongyang Li","url":null},"license":{"name":"CC BY-NC 4.0","url":"https://creativecommons.org/licenses/by-nc/4.0/?spm=5176.12282016.0.0.63b47586Niz8D0"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Natural Language Understanding","url":"/task/natural-language-understanding","datasets_with_task":"/datasets/task/natural-language-understanding"}],"languages":[],"variants":["GeoGLUE"],"data_loaders":[],"num_papers_in_archive":3,"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."}