https://researchdata.se/en/catalogue Search results en Italian restricted part of the dataset from the project DReaM: The Dictionary/Grammar Reading Machine. Wed, 01 Jan 2025 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-23695-7a5w-vx96 https://researchdata.se/en/catalogue/dataset/doi-10-23695-7a5w-vx96 University of Gothenburg Dataset description MultiGEC is a dataset for Multilingual Grammatical Error Correction in 12 European languages (Czech, English, Estonian, German, Greek, Icelandic, Italian, Latvian, Russian, Slovene, Swedish and Ukrainian) compiled by the CompSLA working group and over 20 external data providers in the context of MultiGEC-2025, the first text-level GEC shared task. The MultiGEC dataset is divided into 17 subcorpora covering different languages, domains and correction styles, summarized below. More detailed information about each subcorpus is available as machine-readable metadata, whose format is described . Wed, 01 Jan 2025 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-23695-h9f5-8143 https://researchdata.se/en/catalogue/dataset/doi-10-23695-h9f5-8143 University of Gothenburg 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/en/catalogue/dataset/doi-10-23695-xe7r-k506 https://researchdata.se/en/catalogue/dataset/doi-10-23695-xe7r-k506 University of Gothenburg Volodina, Elena Bryant, Chris Caines, Andrew De Clercq, Orphée Frey, Jennifer-Carmen Ershova, Elizaveta Rosen, Alexandr Vinogradova, Olga Italian open part of the dataset from the project DReaM: The Dictionary/Grammar Reading Machine. Wed, 01 Jan 2025 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-23695-yg34-sy21 https://researchdata.se/en/catalogue/dataset/doi-10-23695-yg34-sy21 University of Gothenburg Part of The Amsterdam Slavic Parallel Aligned Corpus Mon, 01 Jan 2024 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-23695-244c-cs90 https://researchdata.se/en/catalogue/dataset/doi-10-23695-244c-cs90 University of Gothenburg 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/en/catalogue/dataset/doi-10-23695-a5k7-az71 https://researchdata.se/en/catalogue/dataset/doi-10-23695-a5k7-az71 University of Gothenburg Berdicevskis, Aleksandrs The Swedish and Italian parts of European Parliament Proceedings Parallel Corpus, release v3 Fri, 28 Sep 2007 00:00:00 GMT https://researchdata.se/en/catalogue/dataset/doi-10-23695-11xf-x609 https://researchdata.se/en/catalogue/dataset/doi-10-23695-11xf-x609 University of Gothenburg Koehn, Philipp