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).
The collection consists of queries and documents provided by the Qwant search Engine (https://www.qwant.com). The queries, which were issued by the users of Qwant, are based on the selected trending topics. The documents in the collection are the webpages which were selected with respect to these queries using the Qwant click model. Apart from the documents selected using this model, the collection also contains randomly selected documents from the Qwant index.
The collection serves as the official test collection for the 2023 LongEval Information Retrieval Lab (https://clef-longeval.github.io/) organised at CLEF. The collection contains test datasets for two organized sub-tasks: short-term persistence (sub-task A) and long-term persistence (sub-task B). The data for the short-term persistence sub-task was collected over July 2022 and this dataset contains 1,593,376 documents and 882 queries. The data for the long-term persistence sub-task was collected over September 2022 and this dataset consists of 1,081,334 documents and 923 queries. Apart from the original French versions of the webpages and queries, the collection also contains their translations into English.
The collection consists of queries and documents provided by the Qwant search Engine (https://www.qwant.com). The queries, which were issued by the users of Qwant, are based on the selected trending topics. The documents in the collection were selected with respect to these queries using the Qwant click model. Apart from the documents selected using this model, the collection also contains randomly selected documents from the Qwant index. All the data were collected over June 2022. In total, the collection contains 672 train queries, with corresponding 9656 assessments coming from the Qwant click model, and 98 heldout queries. The set of documents consist of 1,570,734 downloaded, cleaned and filtered Web Pages. Apart from their original French versions, the collection also contains translations of the webpages and queries into English. The collection serves as the official training collection for the 2023 LongEval Information Retrieval Lab (https://clef-longeval.github.io/) organised at CLEF.
Mapping table for the article Hajič et al., 2024: Mapping Czech Verbal Valency to PropBank Argument Labels, in LREC-COLING 2024, as preprocess by the algorithm described in the paper. This dataset i smeant for verification (replicatoin) purposes only. It will b manually processed further to arrive at a workable CzezchpropBank, to be used in Czech UMR annotation, to be further updated during the annotation. The resulting PropBank frame files fir Czech are expected to be available with some future releases of UMR, containing Czech UMR annotation, or separately.
The SynSemClass synonym verb lexicon version 5.0 is a multilingual resource that enriches previous editions of this event-type ontology with a new language, Spanish. The existing languages, English, Czech and German, are further substantially extended by a larger number of classes. SSC 5.0 data also contain lists (in a separate removed_cms.zip file) with originally (pre-)proposed but later rejected class members. All languages are organized into classes and have links to other lexical sources. In addition to the existing links, links to Spanish sources have been added.
The Spanish entries are linked to
ADESSE (http://adesse.uvigo.es/),
Spanish SenSem (http://grial.edu.es/sensem/lexico?idioma=en),
Spanish WordNet (https://adimen.si.ehu.es/cgi-bin/wei/public/wei.consult.perl),
AnCora (https://clic.ub.edu/corpus/en/ancoraverb_es), and
Spanish FrameNet (http://sfn.spanishfn.org/SFNreports.php).
The English entries are linked to
EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2),
CzEngVallex (http://hdl.handle.net/11234/1-1512),
FrameNet (https://framenet.icsi.berkeley.edu/)
VerbNet (https://uvi.colorado.edu/ and http://verbs.colorado.edu/verbnet/index.html),
PropBank (http://propbank.github.io/),
Ontonotes (http://clear.colorado.edu/compsem/index.php?page=lexicalresources&sub=ontonotes), and
English Wordnet (https://wordnet.princeton.edu/).
Czech entries are linked to
PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F),
Vallex (http://hdl.handle.net/11234/1-3524), and
CzEngVallex (http://hdl.handle.net/11234/1-1512).
The German entries are linked to
Woxikon (https://synonyme.woxikon.de),
E-VALBU (https://grammis.ids-mannheim.de/verbvalenz), and
GUP (http://alanakbik.github.io/multilingual.html and https://github.com/UniversalDependencies/UD_German-GSD).
Tokenizer, POS Tagger, Lemmatizer and Parser models for 131 treebanks of 72 languages of Universal Depenencies 2.12 Treebanks, created solely using UD 2.12 data (https://hdl.handle.net/11234/1-5150). The model documentation including performance can be found at https://ufal.mff.cuni.cz/udpipe/2/models#universal_dependencies_212_models .
To use these models, you need UDPipe version 2.0, which you can download from https://ufal.mff.cuni.cz/udpipe/2 .
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