This paper presents some experiments for the construction of an high-performance PoS-tagger for Italian using deep neural networks techniques (DNN) integrated with an Italian powerful morphological analyser. The results obtained by the proposed system on standard datasets taken from the EVALITA campaigns show large accuracy improvements when compared with previous systems from the literature.
Tamburini, F. (2016). (Better than) State-of-the-Art PoS-tagging for Italian Texts. Torino : AAccademia University Press.
(Better than) State-of-the-Art PoS-tagging for Italian Texts
TAMBURINI, FABIO
2016
Abstract
This paper presents some experiments for the construction of an high-performance PoS-tagger for Italian using deep neural networks techniques (DNN) integrated with an Italian powerful morphological analyser. The results obtained by the proposed system on standard datasets taken from the EVALITA campaigns show large accuracy improvements when compared with previous systems from the literature.File in questo prodotto:
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