https://researchdata.se/sv/catalogue Search results sv Italiensk del med begränsad åtkomst av datamängden från projektet DReaM: The Dictionary/Grammar Reading Machine. Wed, 01 Jan 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-23695-7a5w-vx96 https://researchdata.se/sv/catalogue/dataset/doi-10-23695-7a5w-vx96 Göteborgs universitet Beskrivning MultiGEC är en datamängd för automatisk korrigering av grammatiska fel -- på engelska Grammatical Error Correction (GEC) -- på 12 olika europeiska språk (tjeckiska, engelska, estniska, tyska, grekiska, isländska, italienska, lettiska, ryska, slovenska, svenska och ukrainska) som sammanställts av CompSLA-arbetsgruppen och över 20 externa dataleverantörer inom ramen för MultiGEC-2025, den första shared task för GEC på textnivå. MultiGEC är indelat i 17 delkorpusar som täcker olika språk, domäner och korrigeringsstilar, vilka sammanfattas nedan. Mer detaljerad information om varje subkorpus finns tillgänglig som maskinläsbara metadata, vars format beskrivs här . Wed, 01 Jan 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-23695-h9f5-8143 https://researchdata.se/sv/catalogue/dataset/doi-10-23695-h9f5-8143 Göteborgs universitet Masciolini, Arianna Caines, Andrew De Clercq, Orphée Kruijsbergen, Joni Kurfali, Murathan Muñoz Sánchez, Ricardo Volodina, Elena Östling, Robert Allkivi-Metsoja, Kais Arhar Holdt, Špela Auzina, Ilze Darģis, Roberts Drakonaki, Elena Frey, Jennifer-Carmen Glišić, Isidora Kikilintza, Pinelopi Nicolas, Lionel Romanyshyn, Mariana Rosen, Alexandr Rozovskaya, Alla Suluste, Kristjan Syvokon, Oleksiy Tantos, Alexandros Touriki, Despoina-Ourania Tsiotskas, Konstantinos Tsourilla, Eleni Varsamopoulos, Vassilis Wisniewski, Katrin Žagar, Aleš Zesch, Torsten Dataset description MultiGED is a dataset for Multilingual Grammatical Error Detection in 5 European languages (Czech, English, German, Italian and Swedish) compiled by the CompSLA working group in the context of MultiGED-2023, the first multilinual GED shared task. The data comes from learner essays, but the sequence of sentences within essays is not kept. Instead, this is a set of randomized sentences to prevent re-construction of original essays. Data is provided in a tab-separated format consisting of two columns, where the first column contains the token and the second column contains the label (c or i), i.e. correct and incorrect. Note that there are no column headers, each sentence is separated by an empty line, and double quotes are escaped. See more on data format . Wed, 01 Jan 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-23695-xe7r-k506 https://researchdata.se/sv/catalogue/dataset/doi-10-23695-xe7r-k506 Göteborgs universitet Volodina, Elena Bryant, Chris Caines, Andrew De Clercq, Orphée Frey, Jennifer-Carmen Ershova, Elizaveta Rosen, Alexandr Vinogradova, Olga Italiensk öppen del av datamängden från projektet DReaM: The Dictionary/Grammar Reading Machine. Wed, 01 Jan 2025 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-23695-yg34-sy21 https://researchdata.se/sv/catalogue/dataset/doi-10-23695-yg34-sy21 Göteborgs universitet Del av The Amsterdam Slavic Parallel Aligned Corpus Mon, 01 Jan 2024 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-23695-244c-cs90 https://researchdata.se/sv/catalogue/dataset/doi-10-23695-244c-cs90 Göteborgs universitet The WordReference corpus is a very large corpus (170M+ words) of native and non-native natural written production in four languages: English, Spanish, French and Italian. It has been scraped from WordReference forums. The corpus consists of four tab-separated files (one per language), each containing seven tab-separated columns: message id, poster's nickname, poster' native language(s), the text of the message (post) itself, the id of the topic in response to which the message has been posted (0 if this message is the topic, i.e. the first in the thread), topicstarter's nickname ("topicstarter" if the poster is the topicstarter), native language of the topicstarter. These are the "raw" data with as little processing as possible (but http links and explicit quotes of other users' posts are removed during the download). Several useful scripts for working with the corpus (including the one which labels all participants as L1 or L2-speakers in the respective subforum) can be found in this repository. For a more detailed description of the corpus, its creation and examples of how it can be used, see the following paper: {publication 297766}. Please cite the paper if you are using the corpus. . Mon, 01 Jan 2024 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-23695-a5k7-az71 https://researchdata.se/sv/catalogue/dataset/doi-10-23695-a5k7-az71 Göteborgs universitet Berdicevskis, Aleksandrs De svenska och italienska delarna av European Parliament Proceedings Parallel Corpus, utgåva v3 Fri, 28 Sep 2007 00:00:00 GMT https://researchdata.se/sv/catalogue/dataset/doi-10-23695-11xf-x609 https://researchdata.se/sv/catalogue/dataset/doi-10-23695-11xf-x609 Göteborgs universitet Koehn, Philipp