Search Results for author: Manuela Sanguinetti

Found 14 papers, 2 papers with code

Content Selection for Explanation Requests in Customer-Care Domain

no code implementations ACL (NL4XAI, INLG) 2020 Luca Anselma, Mirko Di Lascio, Dario Mana, Alessandro Mazzei, Manuela Sanguinetti

This paper describes a content selection module for the generation of explanations in a dialogue system designed for customer care domain.

Annotating Errors and Emotions in Human-Chatbot Interactions in Italian

no code implementations COLING (LAW) 2020 Manuela Sanguinetti, Alessandro Mazzei, Viviana Patti, Marco Scalerandi, Dario Mana, Rossana Simeoni

This paper describes a novel annotation scheme specifically designed for a customer-service context where written interactions take place between a given user and the chatbot of an Italian telecommunication company.

Chatbot Text Generation

Multilingual Irony Detection with Dependency Syntax and Neural Models

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).

Word Embeddings

Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations

no code implementations3 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.

Marking Irony Activators in a Universal Dependencies Treebank: The Case of an Italian Twitter Corpus

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.

Sentiment Analysis

Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies

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.

SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter

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.

Exploiting catenae in a parallel treebank alignment

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.

Translation

The Parallel-TUT: a multilingual and multiformat treebank

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.

Machine Translation

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