Luca Brigada Villa

Also published as: Luca Brigada Villa


2023

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LSDT: a Dependency Treebank of Lombard Sinti
Marco Forlano | Luca Brigada Villa
Proceedings of the Sixth Workshop on the Use of Computational Methods in the Study of Endangered Languages

2022

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UDeasy: a Tool for Querying Treebanks in CoNLL-U Format
Luca Brigada Villa
Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-10)

Many tools are available to query a dependency treebank, but they require the users to know a query language. In this paper I present UDeasy, an application whose main goal is to allow the users to easily query and extract patterns from a dependency treebank in CoNLL-U format.

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Annotating “Absolute” Preverbs in the Homeric and Vedic Treebanks
Luca Brigada Villa | Erica Biagetti | Chiara Zanchi
Proceedings of the Second Workshop on Language Technologies for Historical and Ancient Languages

Indo-European preverbs are uninflected morphemes attaching to verbs and modifying their meaning. In Early Vedic and Homeric Greek, these morphemes held ambiguous morphosyntactic status raising issues for syntactic annotation. This paper focuses on the annotation of preverbs in so-called “absolute” position in two Universal Dependencies treebanks. This issue is related to the broader topic of how to annotate ellipsis in Universal Dependencies. After discussing some of the current annotations, we propose a new scheme that better accounts for the variety of absolute constructions.

2021

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Inferring Morphological Complexity from Syntactic Dependency Networks: A Test
Guglielmo Inglese | Luca Brigada Villa
Proceedings of the Third Workshop on Computational Typology and Multilingual NLP

Research in linguistic typology has shown that languages do not fall into the neat morphological types (synthetic vs. analytic) postulated in the 19th century. Instead, analytic and synthetic must be viewed as two poles of a continuum and languages may show a mix analytic and synthetic strategies to different degrees. Unfortunately, empirical studies that offer a more fine-grained morphological classification of languages based on these parameters remain few. In this paper, we build upon previous research by Liu & Xu (2011) and investigate the possibility of inferring information on morphological complexity from syntactic dependency networks.