CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 1.0 consists of 17 datasets for 11 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 13 datasets for 10 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 1 for Hungarian, 1 for Lithuanian, 1 for Polish, 1 for Russian, and 1 for Spanish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource too. Version 1.0 consists of the same corpora and languages as the previous version 0.2; however, the English GUM dataset has been updated to a newer and larger version, and in the Czech/English PCEDT dataset, the train-dev-test split has been changed to be compatible with OntoNotes. Nevertheless, the main change is in the file format (the MISC attributes have new form and interpretation).
CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 1.1 consists of 21 datasets for 13 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 17 datasets for 12 languages (1 dataset for Catalan, 2 for Czech, 2 for English, 1 for French, 2 for German, 2 for Hungarian, 1 for Lithuanian, 2 for Norwegian, 1 for Polish, 1 for Russian, 1 for Spanish, and 1 for Turkish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource too. Compared to the previous version 1.0, the version 1.1 comprises new languages and corpora, namely Hungarian-KorKor, Norwegian-BokmaalNARC, Norwegian-NynorskNARC, and Turkish-ITCC. In addition, the English GUM dataset has been updated to a newer and larger version, and the conversion pipelines for most datasets have been refined (a list of all changes in each dataset can be found in the corresponding README file).
CorefUD is a collection of previously existing datasets annotated with coreference, which we converted into a common annotation scheme. In total, CorefUD in its current version 1.2 consists of 25 datasets for 16 languages. The datasets are enriched with automatic morphological and syntactic annotations that are fully compliant with the standards of the Universal Dependencies project. All the datasets are stored in the CoNLL-U format, with coreference- and bridging-specific information captured by attribute-value pairs located in the MISC column. The collection is divided into a public edition and a non-public (ÚFAL-internal) edition. The publicly available edition is distributed via LINDAT-CLARIAH-CZ and contains 21 datasets for 15 languages (1 dataset for Ancient Greek, 1 for Ancient Hebrew, 1 for Catalan, 2 for Czech, 3 for English, 1 for French, 2 for German, 2 for Hungarian, 1 for Lithuanian, 2 for Norwegian, 1 for Old Church Slavonic, 1 for Polish, 1 for Russian, 1 for Spanish, and 1 for Turkish), excluding the test data. The non-public edition is available internally to ÚFAL members and contains additional 4 datasets for 2 languages (1 dataset for Dutch, and 3 for English), which we are not allowed to distribute due to their original license limitations. It also contains the test data portions for all datasets. When using any of the harmonized datasets, please get acquainted with its license (placed in the same directory as the data) and cite the original data resource, too. Compared to the previous version 1.1, the version 1.2 comprises new languages and corpora, namely Ancient_Greek-PROIEL, Ancient_Hebrew-PTNK, English-LitBank, and Old_Church_Slavonic-PROIEL. In addition, English-GUM and Turkish-ITCC have been updated to newer versions, conversion of zeros in Polish-PCC has been improved, and the conversion pipelines for multiple other datasets have been refined (a list of all changes in each dataset can be found in the corresponding README file).
The `corpipe23-corefud1.1-231206` is a `mT5-large`-based multilingual model for coreference resolution usable in CorPipe 23 (https://github.com/ufal/crac2023-corpipe). It is released under the CC BY-NC-SA 4.0 license.
The model is language agnostic (no _corpus id_ on input), so it can be used to predict coreference in any `mT5` language (for zero-shot evaluation, see the paper). However, note that the empty nodes must be present already on input, they are not predicted (the same settings as in the CRAC23 shared task).
The Czech translation of SQuAD 2.0 and SQuAD 1.1 datasets contains automatically translated texts, questions and answers from the training set and the development set of the respective datasets.
The test set is missing, because it is not publicly available.
The data is released under the CC BY-NC-SA 4.0 license.
If you use the dataset, please cite the following paper (the exact format was not available during the submission of the dataset): Kateřina Macková and Straka Milan: Reading Comprehension in Czech via Machine Translation and Cross-lingual Transfer, presented at TSD 2020, Brno, Czech Republic, September 8-11 2020.
Grammar Error Correction Corpus for Czech (GECCC) consists of 83 058 sentences and covers four diverse domains, including essays written by native students, informal website texts, essays written by Romani ethnic minority children and teenagers and essays written by nonnative speakers. All domains are professionally annotated for GEC errors in a unified manner, and errors were automatically categorized with a Czech-specific version of ERRANT released at https://github.com/ufal/errant_czech
The dataset was introduced in the paper Czech Grammar Error Correction with a Large and Diverse Corpus that was accepted to TACL. Until published in TACL, see the arXiv version: https://arxiv.org/pdf/2201.05590.pdf
Grammar Error Correction Corpus for Czech (GECCC) consists of 83 058 sentences and covers four diverse domains, including essays written by native students, informal website texts, essays written by Romani ethnic minority children and teenagers and essays written by nonnative speakers. All domains are professionally annotated for GEC errors in a unified manner, and errors were automatically categorized with a Czech-specific version of ERRANT released at https://github.com/ufal/errant_czech
The dataset was introduced in the paper Czech Grammar Error Correction with a Large and Diverse Corpus that was accepted to TACL. Until published in TACL, see the arXiv version: https://arxiv.org/pdf/2201.05590.pdf
This version fixes double annotation errors in train and dev M2 files, and also contains more metadata information.
A richly annotated and genre-diversified language resource, The Prague Dependency Treebank – Consolidated 1.0 (PDT-C 1.0, or PDT-C in short in the sequel) is a consolidated release of the existing PDT-corpora of Czech data, uniformly annotated using the standard PDT scheme. PDT-corpora included in PDT-C: Prague Dependency Treebank (the original PDT contents, written newspaper and journal texts from three genres); Czech part of Prague Czech-English Dependency Treebank (translated financial texts, from English), Prague Dependency Treebank of Spoken Czech (spoken data, including audio and transcripts and multiple speech reconstruction annotation); PDT-Faust (user-generated texts). The difference from the separately published original treebanks can be briefly described as follows: it is published in one package, to allow easier data handling for all the datasets; the data is enhanced with a manual linguistic annotation at the morphological layer and new version of morphological dictionary is enclosed; a common valency lexicon for all four original parts is enclosed. Documentation provides two browsing and editing desktop tools (TrEd and MEd) and the corpus is also available online for searching using PML-TQ.
RobeCzech is a monolingual RoBERTa language representation model trained on Czech data. RoBERTa is a robustly optimized Transformer-based pretraining approach. We show that RobeCzech considerably outperforms equally-sized multilingual and Czech-trained contextualized language representation models, surpasses current state of the art in all five evaluated NLP tasks and reaches state-of-theart results in four of them. The RobeCzech model is released publicly at https://hdl.handle.net/11234/1-3691 and https://huggingface.co/ufal/robeczech-base, both for PyTorch and TensorFlow.