Parallel texts from Swedish Labour market agency. Part 2 (Processed)

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Same as part 1, but with the Readme-file. (Processed)

Resource Type:Corpus
Media Type:Text
Languages:English
Finnish
French
German
Polish
Romanian
Spanish; Castilian
Swedish
Convention on the transfer of sentenced persons (English - Greek) (Processed)

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Convention, additional protocol on the convention, recom...

Resource Type:Corpus
Media Type:Text
Languages:English
Greek, Modern (1453-)
SIP Publications (Processed)

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Publications from the Luxembourgish government edited by...

Resource Type:Corpus
Media Type:Text
Languages:English
French
German
Maltese Fiction Wordlist

This is a wordlist which was created from 32 Maltese fiction books. These texts were originally in PDF file format and were converted to txt format. In the next step, the text file was tokenized and a frequency count was performed on the separate tokens. The resulting list (with about 50,000 entr...

Resource Type:Lexical / Conceptual
Media Type:Text
Language:Maltese
MaltParser

MaltParser is a system for data-driven dependency parsing, which can be used to induce a parsing model from treebank data and to parse new data using an induced model. MaltParser is developed by Johan Hall, Jens Nilsson and Joakim Nivre at Växjö University and Uppsala University, Sweden (see Nivr...

Resource Type:Tool / Service
UIMA/U-Compare GENIA Sentence Detector

The purpose of the tool is to detect sentence boundaries in English text. It is trained on the GENIA corpus of biomedical abstracts and so is particularly suitable for splitting sentences in biomedical texts. The tool is provided as a UIMA component, which forms part of the in-built library of co...

Resource Type:Tool / Service
Language:English
Croatian-English corpus with statistical reports and studies from the Croatian Bureau of Statistics website (Processed)

This dataset has been created within the framework of the European Language Resource Coordination (ELRC) Connecting Europe Facility - Automated Translation (CEF.AT) action. For further information on the project: http://lr-coordination.eu. Croatian-English corpus with statistical reports and stu...

Resource Type:Corpus
Media Type:Text
Languages:Croatian
English
Albertina PT-BR

Albertina PT-* is a foundation, large language model for the Portuguese language. It is an encoder of the BERT family, based on the neural architecture Transformer and developed over the DeBERTa model, and with most competitive performance for this language. It has different versions that were...

Resource Type:Language Description
Media Type:Text
Language:Portuguese
NoSta-D: German NER Dataset Train/Dev

Freely available large dataset, manually annotated for German NER. Includes nested span annotations. Source text from German Wikipedia and news. This data set does not contain the test data, which is used for the GermEval 2014 NER task at KONVENS. Test data will be available from September 2014.

Resource Type:Corpus
Media Type:Text
Language:German
LX-WordSim-353

The LX-WordSim-353 was created from WordSim-353 (Agirre et al., 2009). As the name suggests, this data set contains 353 pairs of words. Both words in each pair can have different morphosyntactic categories. The data set is made of nouns, adjectives, verbs and named entities, and has no multiwords...

Resource Type:Corpus
Media Type:Text
Language:Portuguese

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