{"url":"/dataset/leipzig-corpora","name":"Leipzig Corpora","full_name":null,"description_markdown":"The Leipzig Corpora Collection presents corpora in different languages using the same format and comparable sources. All data are available as plain text files and can be imported into a MySQL database by using the provided import script. They are intended both for scientific use by corpus linguists as well as for applications such as knowledge extraction programs.\r\nThe corpora are identical in format and similar in size and content. They contain randomly selected sentences in the language of the corpus and are available in sizes from 10,000 sentences up to 1 million sentences. The sources are either newspaper texts or texts randomly collected from the web. The texts are split into sentences. Non-sentences and foreign language material was removed. Because word co-occurrence information is useful for many applications, these data are precomputed and included as well. For each word, the most significant words appearing as immediate left or right neighbor or appearing anywhere within the same sentence are given. More information about the format and content of these files can be found here.\r\nThe corpora are automatically collected from carefully selected public sources without considering in detail the content of the contained text. No responsibility is taken for the content of the data. In particular, the views and opinions expressed in specific parts of the data remain exclusively with the authors.\r\n\r\nIf you use one of these corpora in your work we kindly ask you to cite this paper as\r\n\r\nD. Goldhahn, T. Eckart & U. Quasthoff: Building Large Monolingual Dictionaries at the Leipzig Corpora Collection: From 100 to 200 Languages.\r\nIn: Proceedings of the 8th International Language Resources and Evaluation (LREC'12), 2012","description_withheld":null,"homepage":"https://wortschatz.uni-leipzig.de/en/download/Gujarati","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Low-Resource Neural Machine Translation","url":"/task/low-resource-neural-machine-translation","datasets_with_task":"/datasets/task/low-resource-neural-machine-translation"},{"name":"NMT","url":"/task/nmt","datasets_with_task":"/datasets/task/nmt"}],"languages":[{"name":"Gujarati","url":"/datasets/language/gujarati"}],"variants":["Leipzig Corpora"],"data_loaders":[],"num_papers_in_archive":2,"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."}