State-of-the-art Italian dependency parsers based on neural and ensemble systems

In this paper we present a work which aims to test the most advanced, state-of-the-art syntactic dependency parsers based on deep neural networks (DNN) on Italian. We made a large set of experiments by using two Italian treebanks containing different text types downloaded from the Universal Dependen...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Oronzo Antonelli, Fabio Tamburini
Formato:	article
Lenguaje:	EN
Publicado:	Accademia University Press 2019
Materias:	Social Sciences H Computational linguistics. Natural language processing P98-98.5
Acceso en línea:	https://doaj.org/article/cd2f1baef5c24e0288441613f6020325
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:cd2f1baef5c24e0288441613f6020325
record_format	dspace
spelling	oai:doaj.org-article:cd2f1baef5c24e0288441613f60203252021-12-02T09:52:22ZState-of-the-art Italian dependency parsers based on neural and ensemble systems2499-455310.4000/ijcol.454https://doaj.org/article/cd2f1baef5c24e0288441613f60203252019-06-01T00:00:00Zhttp://journals.openedition.org/ijcol/454https://doaj.org/toc/2499-4553In this paper we present a work which aims to test the most advanced, state-of-the-art syntactic dependency parsers based on deep neural networks (DNN) on Italian. We made a large set of experiments by using two Italian treebanks containing different text types downloaded from the Universal Dependencies project and propose a new solution based on ensemble systems. We implemented the proposed ensemble solutions by testing different techniques described in literature, obtaining very good parsing results, well above the state of the art for Italian.Oronzo AntonelliFabio TamburiniAccademia University PressarticleSocial SciencesHComputational linguistics. Natural language processingP98-98.5ENIJCoL, Vol 5, Iss 1, Pp 33-55 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Social Sciences H Computational linguistics. Natural language processing P98-98.5
spellingShingle	Social Sciences H Computational linguistics. Natural language processing P98-98.5 Oronzo Antonelli Fabio Tamburini State-of-the-art Italian dependency parsers based on neural and ensemble systems
description	In this paper we present a work which aims to test the most advanced, state-of-the-art syntactic dependency parsers based on deep neural networks (DNN) on Italian. We made a large set of experiments by using two Italian treebanks containing different text types downloaded from the Universal Dependencies project and propose a new solution based on ensemble systems. We implemented the proposed ensemble solutions by testing different techniques described in literature, obtaining very good parsing results, well above the state of the art for Italian.
format	article
author	Oronzo Antonelli Fabio Tamburini
author_facet	Oronzo Antonelli Fabio Tamburini
author_sort	Oronzo Antonelli
title	State-of-the-art Italian dependency parsers based on neural and ensemble systems
title_short	State-of-the-art Italian dependency parsers based on neural and ensemble systems
title_full	State-of-the-art Italian dependency parsers based on neural and ensemble systems
title_fullStr	State-of-the-art Italian dependency parsers based on neural and ensemble systems
title_full_unstemmed	State-of-the-art Italian dependency parsers based on neural and ensemble systems
title_sort	state-of-the-art italian dependency parsers based on neural and ensemble systems
publisher	Accademia University Press
publishDate	2019
url	https://doaj.org/article/cd2f1baef5c24e0288441613f6020325
work_keys_str_mv	AT oronzoantonelli stateoftheartitaliandependencyparsersbasedonneuralandensemblesystems AT fabiotamburini stateoftheartitaliandependencyparsersbasedonneuralandensemblesystems
_version_	1718397969937465344

State-of-the-art Italian dependency parsers based on neural and ensemble systems

Ejemplares similares