The text of the novel Sania (eng. The Sledge) served as a training corpus. It was written in 1955 by Ion Druță and printed originally in Cyrillic scripts. We have followed a special previously developed technology of recognition and specialized lexicons. In such a way, we have obtained the electr...
The BioLexicon is a large-scale, wide-coverage computational lexicon covering the biomedical domain. A large part of the lexicon is concerned with covering biomedical terms and their variants. Entries for domain-specific verbs include syntactic and semantic information. The lexicon includes entri...
The QTLeap corpus is composed by 4000 question and answer pairs in the domain of computer and IT troubleshooting for both hardware and software. This material was collected using a support service via chat, this implies that the corpus is composed by naturally occurring utterances produced by use...
GREC is a semantically annotated corpus of 240 MEDLINE abstracts (167 on the subject of E. coli species and 73 on the subject of the Human species) which is intended for training IE systems and/or resources which are used to extract events from biomedical literature.
The corpus contains the Laws of Malta in English from the official government website. The unannotated raw text files were extracted from the pdf files that can be found on the website.
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...
A corpus of 2,000 MEDLINE abstracts, collected using the three MeSH terms human, blood cells and transcription factors. The corpus is available in three formats: 1) A text file containing part-of-speech (POS) annotation, based on the Penn Treebank format, 2) An XML file containing inline POS anno...
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.
Bilingual (EN-PT) corpus acquired from the website https://antibiotic.ecdc.europa.eu/
Bulgarian-English Wikipedia WSD/NED corpus is composed of articles from the Bulgarian version of Wikipedia and their English counterparts.