In this paper we present an automatic multilingual annotation of theWikipedia dumps in two languages, with both word senses (i.e. concepts) and named entities. We use Babelfy 1.0, a state-of-the-art multilingual Word Sense Disambiguation and Entity Linking system. As its reference inventory, Babelfy draws upon BabelNet 3.0, a very large multilingual encyclopedic dictionary and semantic network which connects concepts and named entities in 271 languages from different inventories, such as WordNet, Open Multilingual WordNet, Wikipedia, OmegaWiki, Wiktionary and Wikidata. In addition, we perform both an automatic evaluation of the dataset and a language-specific statistical analysis. In detail, we investigate the word sense distributions by part-of-speech and language, together with the similarity of the annotated entities and concepts for a random sample of interlinked Wikipedia pages in different languages. The annotated corpora are available at http://lcl.uniroma1.it/babelfied-wikipedia/.
Scozzafava, F., Raganato, A., Moro, A., Navigli, R. (2015). Automatic identification and disambiguation of concepts and named entities in the multilingual wikipedia. In AI*IA 2015 Advances in Artificial Intelligence (pp.357-366). Springer Verlag [10.1007/978-3-319-24309-2_27].
Automatic identification and disambiguation of concepts and named entities in the multilingual wikipedia
Raganato A
;
2015
Abstract
In this paper we present an automatic multilingual annotation of theWikipedia dumps in two languages, with both word senses (i.e. concepts) and named entities. We use Babelfy 1.0, a state-of-the-art multilingual Word Sense Disambiguation and Entity Linking system. As its reference inventory, Babelfy draws upon BabelNet 3.0, a very large multilingual encyclopedic dictionary and semantic network which connects concepts and named entities in 271 languages from different inventories, such as WordNet, Open Multilingual WordNet, Wikipedia, OmegaWiki, Wiktionary and Wikidata. In addition, we perform both an automatic evaluation of the dataset and a language-specific statistical analysis. In detail, we investigate the word sense distributions by part-of-speech and language, together with the similarity of the annotated entities and concepts for a random sample of interlinked Wikipedia pages in different languages. The annotated corpora are available at http://lcl.uniroma1.it/babelfied-wikipedia/.
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