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...
محفوظ في:
| الحاوية / القاعدة: | URI:https://journals.openedition.org/ijcol, |
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| المؤلفون الرئيسيون: | , |
| التنسيق: | Article ou chapitre numérique |
| اللغة: | Anglais |
| منشور في: |
IJCoL
2020
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| الوصول للمادة أونلاين: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |
| الملخص: | 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. |
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