1 code implementation • LT4HALA (LREC) 2022 • Alessio Palmero Aprosio, Stefano Menini, Sara Tonelli
This has led to the creation of BERT-like models for different languages trained with digital repositories from the past.
1 code implementation • EMNLP 2021 • Elisa Leonardelli, Stefano Menini, Alessio Palmero Aprosio, Marco Guerini, Sara Tonelli
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
1 code implementation • LREC 2022 • Teresa Paccosi, Alessio Palmero Aprosio
The dataset (around 600K tokens) mostly contains manual gold annotations in three different domains (news, literature, and political discourses) and a semi-automatically annotated part.
no code implementations • 28 Sep 2021 • Elisa Leonardelli, Stefano Menini, Alessio Palmero Aprosio, Marco Guerini, Sara Tonelli
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
no code implementations • ACL 2021 • Valentino Frasnelli, Lorenzo Bocchi, Alessio Palmero Aprosio
In this paper, we present Tintful, an NLP annotation software that can be used both to manually annotate texts and to fix mistakes in NLP pipelines, such as Stanford CoreNLP.
no code implementations • EACL 2021 • Lorenzo Bocchi, Valentino Frasnelli, Alessio Palmero Aprosio
Amazon Mechanical Turk (AMT) has recently become one of the most popular crowd-sourcing platforms, allowing researchers from all over the world to create linguistic datasets quickly and at a relatively low cost.
1 code implementation • 27 Mar 2021 • Stefano Menini, Alessio Palmero Aprosio, Sara Tonelli
We first re-annotate part of a widely used dataset for abusive language detection in English in two conditions, i. e. with and without context.
1 code implementation • SEMEVAL 2020 • Camilla Casula, Alessio Palmero Aprosio, Stefano Menini, Sara Tonelli
In this paper we present our submission to sub-task A at SemEval 2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval2).
no code implementations • 5 May 2020 • Alessio Palmero Aprosio, Stefano Menini, Sara Tonelli
We find that users judge the same images in different ways, although the presence of a person in the picture increases the probability to get an offensive comment.
no code implementations • LREC 2020 • Daniela Trotta, Alessio Palmero Aprosio, Sara Tonelli, Annibale Elia
This paper introduces a multimodal corpus in the political domain, which on top of transcribed face-to-face interviews presents the annotation of facial displays, hand gestures and body posture.
no code implementations • WS 2019 • Alessio Palmero Aprosio, Sara Tonelli, Marco Turchi, Matteo Negri, Mattia A. Di Gangi
Inspired by the machine translation field, in which synthetic parallel pairs generated from monolingual data yield significant improvements to neural models, in this paper we exploit large amounts of heterogeneous data to automatically select simple sentences, which are then used to create synthetic simplification pairs.
no code implementations • IJCNLP 2017 • Carolina Scarton, Alessio Palmero Aprosio, Sara Tonelli, Tamara Mart{\'\i}n Wanton, Lucia Specia
Our implementation includes a set of general-purpose simplification rules, as well as a sentence selection module (to select sentences to be simplified) and a confidence model (to select only promising simplifications).
no code implementations • 1 Dec 2016 • Stefano Borgo, Loris Bozzato, Alessio Palmero Aprosio, Marco Rospocher, Luciano Serafini
Systems for automatic extraction of semantic information about events from large textual resources are now available: these tools are capable to generate RDF datasets about text extracted events and this knowledge can be used to reason over the recognized events.
1 code implementation • 20 Sep 2016 • Alessio Palmero Aprosio, Giovanni Moretti
In this we paper present Tint, an easy-to-use set of fast, accurate and extendable Natural Language Processing modules for Italian.
no code implementations • LREC 2016 • Francesco Corcoglioniti, Marco Rospocher, Alessio Palmero Aprosio, Sara Tonelli
We introduce PreMOn (predicate model for ontologies), a linguistic resource for exposing predicate models (PropBank, NomBank, VerbNet, and FrameNet) and mappings between them (e. g, SemLink) as Linked Open Data.