Andrea Di Fabio

Also published as: Andrea Di Fabio


2025

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LiITA: a Knowledge Base of Interoperable Resources for Italian
Eleonora Litta | Marco Carlo Passarotti | Valerio Basile | Cristina Bosco | Andrea Di Fabio | Paolo Brasolin
Proceedings of the 5th Conference on Language, Data and Knowledge

31 This paper describes the LiITA Knowledge Base of interoperable linguistic resources for Italian.By adhering to the Linked Open Data principles, LiITA ensures and facilitates interoperability between distributed resources. The paper outlines the lemma-centered architecture of the Knowledge Base and details its core component: the Lemma Bank, a collection of Italian lemmas designed to interlink distributed lexical and textual resources.

2024

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The Lemma Bank of the LiITA Knowledge Base of Interoperable Resources for Italian
Eleonora Litta | Marco Passarotti | Paolo Brasolin | Giovanni Moretti | Valerio Basile | Andrea Di Fabio | Cristina Bosco
Proceedings of the 10th Italian Conference on Computational Linguistics (CLiC-it 2024)

The paper introduces the LiIta Knowledge Base of interoperable linguistic resources for Italian. After describing the principles of the Linked Data paradigm, on which LiIta is grounded, the paper presents the lemma-centred architecture of the Knowledge Base and details its core component, consisting of a large collection of Italian lemmas (called the Lemma Bank) used to interlink distributed lexical and textual resources.

2019

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VerbAtlas: a Novel Large-Scale Verbal Semantic Resource and Its Application to Semantic Role Labeling
Andrea Di Fabio | Simone Conia | Roberto Navigli
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

We present VerbAtlas, a new, hand-crafted lexical-semantic resource whose goal is to bring together all verbal synsets from WordNet into semantically-coherent frames. The frames define a common, prototypical argument structure while at the same time providing new concept-specific information. In contrast to PropBank, which defines enumerative semantic roles, VerbAtlas comes with an explicit, cross-frame set of semantic roles linked to selectional preferences expressed in terms of WordNet synsets, and is the first resource enriched with semantic information about implicit, shadow, and default arguments. We demonstrate the effectiveness of VerbAtlas in the task of dependency-based Semantic Role Labeling and show how its integration into a high-performance system leads to improvements on both the in-domain and out-of-domain test sets of CoNLL-2009. VerbAtlas is available at http://verbatlas.org.