This tool assigns a part-of-speech tag and base form to each token in a text. It operates on text that has previously been tokenised and morphologically analysed. The POS tagger is a module of Apertium machine translation system. The provided tool can currently operate on a subset of the language...
This tool translates text from a source language into a target language. It operates on text that has previously been tokenised and morphologically analysed, and POS-tagged. Target language tokens are assigned POS tags and morphological analyses. The Apertium Translator is a module of Apertium ma...
This tool performs tokenization of text and assigns all possible morphological analyses to each token. These analyses include the base form of the token, part-of-speech, information about number and gender. The morphological analyser is a module of Apertium machine translation system. The provide...
This resource is part of Deliverable 4.6 of the QTLeap FP7 project (Contract number 610516). In its current development (15% of the intended goal of the project), it is composed of 150 sentences (1,416 English tokens and 1,275 Basque tokens). The sentences are excerpts from journalistic text from...
Terms that have (more or less) recently been accepted and normalised by Termcat, mixed fields
Industry terms
Corpus of raw and manual post-edited translations (50.204 words). It was created by manual post-editing of the Basque outputs given by Matxin RBMT system translating 100 entries from the Spanish Wikipedia.
This corpus is created from documents from translation memorios of Elhuyar Fundation (obtained via Eleka, member of the Advisory Board of Potential Users).
ixa-pipe-coref-eu is a Basque coreference resolution tool, which is an adaptation of Stanford Deterministic Coreference Resolution (http://www-nlp.stanford.edu/downloads/dcoref.shtml). This tool reads a text document annotated with lemmas, named entities and constituents formated in Natural La...
Europarl QTLeap WSD/NED corpus This corpora is part of Deliverable 5.5 of the European Commission project QTLeap FP7-ICT-2013.4.1-610516 (http://qtleap.eu). The texts are sentences from the Europarl parallel corpus (Koehn, 2005). We selected the monolingual sentences from parallel corpora ...