Exploring the Betrothed Lovers

We present the ongoing activities and the first results achieved in a research project concerning the understanding of narrative in the high school. Students and teachers experimented with new ways to learn linguistic and digital skills, by using a collaborative learning environment built around the novel I Promessi Sposi. We analyzed the literary text, extracting social networks of characters and other fundamental narrative elements (sequences, locations, etc.), in order to provide the students with appropriate tools and resources to conduct their own inquiries on the novel

Overview of the EVALITA 2016 Part of speech on twitter for Italian task

The increasing interest for the extraction of various forms of knowledge from micro-blogs and social media makes crucial the development of resources and tools that can be used for automatically deal with them. PoSTWITA contributes to the advancement of the state-of-the-art for Italian language by: (a) enriching the community with a previously not existing col- lection of data extracted from Twitter and annotated with grammatical categories, to be used as a benchmark for system evaluation; (b) supporting the adaptation of Part of Speech tagging systems to this particular text domain

A Complementary Account to Emotion Extraction and Classification in Cultural Heritage Based on the Plutchik’s Theory

The paper presents a combined approach to knowledge-based emotion attribution and classification of cultural items employed in the H2020 project SPICE. In particular, we show a preliminary experimentation conducted on a selection of items contributed by the GAM Museum in Turin (Galleria di Arte Moderna), pointing out how different language-based approaches to emotion categorization (used in the systems Sophia and DEGARI respectively) can be powerfully combined to cope with both coverage and extended affective attributions. Interestingly, both approaches are based on an ontology of the Plutchik’s theory of emotions

La summarization di testi giuridici: una sperimentazione con GPT-3

Nel presente saggio, dopo una breve presentazione dei modelli linguistici BERT e GPT-3, viene discussa la possibilità di usare l’intelligenza artificiale per aumentare le capacità di comunicare l’informazione giuridica e in particolare le informazioni provenienti dal legislatore e dal funzionario addetto alla redazione di testi amministrativi. In particolare viene illustrato come il modello GPT-3 è stato testato su un set eterogeneo di atti amministrativi e di norme di vario livello, per valutare la sua capacità di riassumerne il contenuto. Gli autori, esperti di linguistica computazionale e giuristi, riportano in dettaglio il caso d’uso progettato, gli output del sistema e le relative valutazioni