Manuela Sanguinetti


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Content Selection for Explanation Requests in Customer-Care Domain
Luca Anselma | Mirko Di Lascio | Dario Mana | Alessandro Mazzei | Manuela Sanguinetti
2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence

This paper describes a content selection module for the generation of explanations in a dialogue system designed for customer care domain. First we describe the construction of a corpus of a dialogues containing explanation requests from customers to a virtual agent of a telco, and second we study and formalize the importance of a specific information content for the generated message. In particular, we adapt the notions of importance and relevance in the case of schematic knowledge bases.

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Multilingual Irony Detection with Dependency Syntax and Neural Models
Alessandra Teresa Cignarella | Valerio Basile | Manuela Sanguinetti | Cristina Bosco | Paolo Rosso | Farah Benamara
Proceedings of the 28th International Conference on Computational Linguistics

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). It focuses on the contribution from syntactic knowledge, exploiting linguistic resources where syntax is annotated according to the Universal Dependencies scheme. Three distinct experimental settings are provided. In the first, a variety of syntactic dependency-based features combined with classical machine learning classifiers are explored. In the second scenario, two well-known types of word embeddings are trained on parsed data and tested against gold standard datasets. In the third setting, dependency-based syntactic features are combined into the Multilingual BERT architecture. The results suggest that fine-grained dependency-based syntactic information is informative for the detection of irony.

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Marking Irony Activators in a Universal Dependencies Treebank: The Case of an Italian Twitter Corpus
Alessandra Teresa Cignarella | Manuela Sanguinetti | Cristina Bosco | Paolo Rosso
Proceedings of the Twelfth Language Resources and Evaluation Conference

The recognition of irony is a challenging task in the domain of Sentiment Analysis, and the availability of annotated corpora may be crucial for its automatic processing. 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. As our case study we therefore introduce a recently released Universal Dependencies treebank for Italian which includes ironic tweets: TWITTIRÒ-UD. For the purposes of this study, we enriched the existing annotation in the treebank, with a further level that includes irony activators. A description and discussion of the annotation scheme is provided with a definition of irony activators and the guidelines for their annotation. This qualitative study on the different layers of annotation applied on the same dataset can shed some light on the process of human annotation, and irony annotation in particular, and on the usefulness of this representation for developing computational models of irony to be used for training purposes.

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Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies
Manuela Sanguinetti | Cristina Bosco | Lauren Cassidy | Özlem Çetinoğlu | Alessandra Teresa Cignarella | Teresa Lynn | Ines Rehbein | Josef Ruppenhofer | Djamé Seddah | Amir Zeldes
Proceedings of the Twelfth Language Resources and Evaluation Conference

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. Given on the one hand the increasing number of treebanks featuring user-generated content, and its somewhat inconsistent treatment in these resources on the other, the aim of this paper is twofold: (1) to provide a short, though comprehensive, overview of such treebanks - based on available literature - along with their main features and a comparative analysis of their annotation criteria, and (2) to propose a set of tentative UD-based annotation guidelines, to promote consistent treatment of the particular phenomena found in these types of texts. The main goal of this paper is to provide a common framework for those teams interested in developing similar resources in UD, thus enabling cross-linguistic consistency, which is a principle that has always been in the spirit of UD.

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Annotating Errors and Emotions in Human-Chatbot Interactions in Italian
Manuela Sanguinetti | Alessandro Mazzei | Viviana Patti | Marco Scalerandi | Dario Mana | Rossana Simeoni
Proceedings of the 14th Linguistic Annotation Workshop

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. More specifically, the scheme aims to detect and highlight two aspects: the presence of errors in the conversation on both sides (i.e. customer and chatbot) and the “emotional load” of the conversation. This can be inferred from the presence of emotions of some kind (especially negative ones) in the customer messages, and from the possible empathic responses provided by the agent. The dataset annotated according to this scheme is currently used to develop the prototype of a rule-based Natural Language Generation system aimed at improving the chatbot responses and the customer experience overall.


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SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
Valerio Basile | Cristina Bosco | Elisabetta Fersini | Debora Nozza | Viviana Patti | Francisco Manuel Rangel Pardo | Paolo Rosso | Manuela Sanguinetti
Proceedings of the 13th International Workshop on Semantic Evaluation

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. The task is organized in two related classification subtasks: a main binary subtask for detecting the presence of hate speech, and a finer-grained one devoted to identifying further features in hateful contents such as the aggressive attitude and the target harassed, to distinguish if the incitement is against an individual rather than a group. HatEval has been one of the most popular tasks in SemEval-2019 with a total of 108 submitted runs for Subtask A and 70 runs for Subtask B, from a total of 74 different teams. Data provided for the task are described by showing how they have been collected and annotated. Moreover, the paper provides an analysis and discussion about the participant systems and the results they achieved in both subtasks.


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PoSTWITA-UD: an Italian Twitter Treebank in Universal Dependencies
Manuela Sanguinetti | Cristina Bosco | Alberto Lavelli | Alessandro Mazzei | Oronzo Antonelli | Fabio Tamburini
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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An Italian Twitter Corpus of Hate Speech against Immigrants
Manuela Sanguinetti | Fabio Poletto | Cristina Bosco | Viviana Patti | Marco Stranisci
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


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Annotating Italian Social Media Texts in Universal Dependencies
Manuela Sanguinetti | Cristina Bosco | Alessandro Mazzei | Alberto Lavelli | Fabio Tamburini
Proceedings of the Fourth International Conference on Dependency Linguistics (Depling 2017)

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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
Daniel Zeman | Martin Popel | Milan Straka | Jan Hajič | Joakim Nivre | Filip Ginter | Juhani Luotolahti | Sampo Pyysalo | Slav Petrov | Martin Potthast | Francis Tyers | Elena Badmaeva | Memduh Gokirmak | Anna Nedoluzhko | Silvie Cinková | Jan Hajič jr. | Jaroslava Hlaváčová | Václava Kettnerová | Zdeňka Urešová | Jenna Kanerva | Stina Ojala | Anna Missilä | Christopher D. Manning | Sebastian Schuster | Siva Reddy | Dima Taji | Nizar Habash | Herman Leung | Marie-Catherine de Marneffe | Manuela Sanguinetti | Maria Simi | Hiroshi Kanayama | Valeria de Paiva | Kira Droganova | Héctor Martínez Alonso | Çağrı Çöltekin | Umut Sulubacak | Hans Uszkoreit | Vivien Macketanz | Aljoscha Burchardt | Kim Harris | Katrin Marheinecke | Georg Rehm | Tolga Kayadelen | Mohammed Attia | Ali Elkahky | Zhuoran Yu | Emily Pitler | Saran Lertpradit | Michael Mandl | Jesse Kirchner | Hector Fernandez Alcalde | Jana Strnadová | Esha Banerjee | Ruli Manurung | Antonio Stella | Atsuko Shimada | Sookyoung Kwak | Gustavo Mendonça | Tatiana Lando | Rattima Nitisaroj | Josie Li
Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

The Conference on Computational Natural Language Learning (CoNLL) features a shared task, in which participants train and test their learning systems on the same data sets. In 2017, the task was devoted to learning dependency parsers for a large number of languages, in a real-world setting without any gold-standard annotation on input. All test sets followed a unified annotation scheme, namely that of Universal Dependencies. In this paper, we define the task and evaluation methodology, describe how the data sets were prepared, report and analyze the main results, and provide a brief categorization of the different approaches of the participating systems.


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Exploiting catenae in a parallel treebank alignment
Manuela Sanguinetti | Cristina Bosco | Loredana Cupi
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

This paper aims to introduce the issues related to the syntactic alignment of a dependency-based multilingual parallel treebank, ParTUT. Our approach to the task starts from a lexical mapping and then attempts to expand it using dependency relations. In developing the system, however, we realized that the only dependency relations between the individual nodes were not sufficient to overcome some translation divergences, or shifts, especially in the absence of a direct lexical mapping and a different syntactic realization. For this purpose, we explored the use of a novel syntactic notion introduced in dependency theoretical framework, i.e. that of catena (Latin for “chain”), which is intended as a group of words that are continuous with respect to dominance. In relation to the task of aligning parallel dependency structures, catenae can be used to explain and identify those cases of one-to-many or many-to-many correspondences, typical of several translation shifts, that cannot be detected by means of direct word-based mappings or bare syntactic relations. The paper presented here describes the overall structure of the alignment system as it has been currently designed, how catenae are extracted from the parallel resource, and their potential relevance to the completion of tree alignment in ParTUT sentences.


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Dependency and Constituency in Translation Shift Analysis
Manuela Sanguinetti | Cristina Bosco | Leonardo Lesmo
Proceedings of the Second International Conference on Dependency Linguistics (DepLing 2013)


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The Parallel-TUT: a multilingual and multiformat treebank
Cristina Bosco | Manuela Sanguinetti | Leonardo Lesmo
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

The paper introduces an ongoing project for the development of a parallel treebank for Italian, English and French, i.e. Parallel--TUT, or simply ParTUT. For the development of this resource, both the dependency and constituency-based formats of the Italian Turin University Treebank (TUT) have been applied to a preliminary dataset, which includes the whole text of the Universal Declaration of Human Rights, and sentences from the JRC-Acquis Multilingual Parallel Corpus and the Creative Commons licence. The focus of the project is mainly on the quality of the annotation and the investigation of some issues related to the alignment of data that can be allowed by the TUT formats, also taking into account the availability of conversion tools for display data in standard ways, such as Tiger--XML and CoNLL formats. It is, in fact, our belief that increasing the portability of our treebank could give us the opportunity to access resources and tools provided by other research groups, especially at this stage of the project, where no particular tool -- compatible with the TUT format -- is available in order to tackle the alignment problems.


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Building the multilingual TUT parallel treebank
Manuela Sanguinetti | Cristina Bosco
Proceedings of the Second Workshop on Annotation and Exploitation of Parallel Corpora