no code implementations • LREC 2022 • Valerio Basile, Cristina Bosco, Michael Fell, Viviana Patti, Rossella Varvara
The European Language Grid enables researchers and practitioners to easily distribute and use NLP resources and models, such as corpora and classifiers.
no code implementations • insights (ACL) 2022 • Alessandra Teresa Cignarella, Cristina Bosco, Paolo Rosso
Furthermore, we study the phenomenon of stance with respect to six different targets – one per language, and two different for Italian – employing a variety of machine learning algorithms that primarily exploit morphological and syntactic knowledge as features, represented throughout the format of Universal Dependencies.
no code implementations • SALLD (LREC) 2022 • Marco A. Stranisci, Simona Frenda, Mirko Lai, Oscar Araque, Alessandra T. Cignarella, Valerio Basile, Viviana Patti, Cristina Bosco
The paper is structured as follows.
1 code implementation • COLING 2020 • Alessandra Teresa Cignarella, Valerio Basile, Manuela Sanguinetti, Cristina Bosco, Paolo Rosso, Farah Benamara
This paper presents an in-depth investigation of the effectiveness of dependency-based syntactic features on the irony detection task in a multilingual perspective (English, Spanish, French and Italian).
no code implementations • 3 Nov 2020 • Manuela Sanguinetti, Lauren Cassidy, Cristina Bosco, Özlem Çetinoğlu, Alessandra Teresa Cignarella, Teresa Lynn, Ines Rehbein, Josef Ruppenhofer, Djamé Seddah, Amir Zeldes
This article presents a discussion on the main linguistic phenomena which cause difficulties in the analysis of user-generated texts found on the web and in social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework of syntactic analysis.
no code implementations • LREC 2020 • Aless Cignarella, ra Teresa, Manuela Sanguinetti, Cristina Bosco, Paolo Rosso
In this paper we describe a fine-grained annotation scheme centered on irony, in which we highlight the tokens that are responsible for its activation, (irony activators) and their morpho-syntactic features.
no code implementations • LREC 2020 • Manuela Sanguinetti, Cristina Bosco, Lauren Cassidy, {\"O}zlem {\c{C}}etino{\u{g}}lu, Aless Cignarella, ra Teresa, Teresa Lynn, Ines Rehbein, Josef Ruppenhofer, Djam{\'e} Seddah, Amir Zeldes
The paper presents a discussion on the main linguistic phenomena of user-generated texts found in web and social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework.
no code implementations • SEMEVAL 2019 • Bilal Ghanem, Aless Cignarella, ra Teresa, Cristina Bosco, Paolo Rosso, Francisco Manuel Rangel Pardo
In the present paper we describe the UPV-28-UNITO system{'}s submission to the RumorEval 2019 shared task.
no code implementations • SEMEVAL 2019 • Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza, Viviana Patti, Francisco Manuel Rangel Pardo, Paolo Rosso, Manuela Sanguinetti
The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in Spanish and English messages extracted from Twitter.
no code implementations • EACL 2017 • Jihen Karoui, Farah Benamara, V{\'e}ronique Moriceau, Viviana Patti, Cristina Bosco, Nathalie Aussenac-Gilles
This paper provides a linguistic and pragmatic analysis of the phenomenon of irony in order to represent how Twitter{'}s users exploit irony devices within their communication strategies for generating textual contents.
no code implementations • LREC 2016 • Cristina Bosco, Mirko Lai, Viviana Patti, Daniela Virone
The annotation process is presented and the disagreement discussed, in particular, in the perspective of figurative language use and in that of the semantic oriented annotation, which are open challenges for NLP systems.
no code implementations • LREC 2016 • Marco Stranisci, Cristina Bosco, Delia Iraz{\'u} Hern{\'a}ndez Far{\'\i}as, Viviana Patti
In this paper we present the TWitterBuonaScuola corpus (TW-BS), a novel Italian linguistic resource for Sentiment Analysis, developed with the main aim of analyzing the online debate on the controversial Italian political reform {``}Buona Scuola{''} (Good school), aimed at reorganizing the national educational and training systems.
no code implementations • LREC 2014 • Maria Simi, Cristina Bosco, Simonetta Montemagni
This is done by comparing the performance of a statistical parser (DeSR) trained on a simpler resource (the augmented version of the Merged Italian Dependency Treebank or MIDT+) and whose output was automatically converted to SD, with the results of the parser directly trained on ISDT.
no code implementations • LREC 2014 • Manuela Sanguinetti, Cristina Bosco, Loredana Cupi
This paper aims to introduce the issues related to the syntactic alignment of a dependency-based multilingual parallel treebank, ParTUT.
no code implementations • LREC 2012 • Cristina Bosco, Manuela Sanguinetti, Leonardo Lesmo
The paper introduces an ongoing project for the development of a parallel treebank for Italian, English and French, i. e.
no code implementations • LREC 2012 • Anita Alicante, Cristina Bosco, Anna Corazza, Alberto Lavelli
The aim of this paper is to contribute to the debate on the issues raised by Morphologically Rich Languages, and more precisely to investigate, in a cross-paradigm perspective, the influence of the constituent order on the data-driven parsing of one of such languages(i. e. Italian).