Resultados de investigación

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This folder contains files for bilingual glossary creation from factored phrase tables that include part of speech tagged text for for FR-EN language pair. The tables are firstly filtered using part of speech tag sequences for each language so that entries with unsuitable part of speech sequences are filtered out. Then, feature scores from the phrase table are combined in a log-linear model to score each entry. The user specifies how large the output glossary should be (relative to the input) and the bottom ranking entries are discarded to produce the desired size glossary.

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We present a set of Spanish gold-standards for different noun classes created in PANACEA to train and test automatic classifiers. To create these gold-standards we used the Spanish working lexicon of the Incyta Machine Translation system (Alonso and Bocsák, 2005) to create the abstract, human, location, process, artifact, matter, semiotic and social gold-standard lists. The gold standard for event nouns (non-deverbal eventive nouns) was developed for the experiments of Bel et al. (2010). These gold-standards were created in the context of PANACEA (http://www.panacea-lr.eu), an EU-FP7 Funded Project under Grant Agreement 248064.

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This data set contains French word n-grams and French word/tag/lemma n-grams in the "Environment" (ENV) domain. N-grams are accompanied by their observed frequency counts. The length of the n-grams ranges from unigrams (single words) to five-grams. The data were collected in the context of PANACEA (http://www.panacea-lr.eu), an EU-FP7 Funded Project under Grant Agreement 248064. The n-gram counts were generated from crawled Web pages that were automatically detected to be in the French language and were automatically classified as relevant to the ENV domain. The ENV domain collection used consisted of approximately 47.3 million tokens. Data collection took place in the summer of 2011.

The PANACEA_SCF_IT_ENV is an automatically created lexicon of verbal subcategorisation frames for 26 verb lemmas. The language is Italian and the domain is Environment. The lexicon was acquired from a monolingual corpus automatically crawled, normalised, cleaned, and NLP processed (Corpus name: PANACEA Annotated Italian Environment Corpus Version 2, PANACEA_MCv2_IT_ENV).

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PANACEA Annotated Spanish Labour Legislation Corpus Version 2 consists of Spanish texts in the Labour legislation (LAB) domain that were collected and automatically annotated in the framework of PANACEA (http://www.panacea-lr.eu), an EU-FP7 Funded Project under Grant Agreement 248064. The texts were crawled web pages that were automatically detected to be in the Spanish language and were automatically classified as relevant to the LAB domain. Data collection took place in the summer of 2011. The automatically assigned annotations deal with sentence and token segmentation, POS and lemma, dependency relations and named entities.