Automatic text coherence modelling plays a crucial role in natural language processing tasks, such as machine translation, summarisation, and question answering. Moreover, text coherence is fundamental to reading comprehension and readers’ engagement, essential to a number of application domains. In this report, we report progress for the Assessing Discourse Coherence in Italian Texts task from EVALITA-23, whose goal is to address automatic coherence detection. The task was challenged by extracting linguistic features used to train a machine learning classifier, leading to minor improvement over the baseline. The feature importance ana
MPG at DisCoTex: Predicting text coherence by treebased modelling of linguistic features / Galletti, Martina; Gravino, Pietro; Prevedello, Giulio. - (2023). (Intervento presentato al convegno 8th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, September 07–08, 2023, Parma, Italy tenutosi a Parma, Italy).
MPG at DisCoTex: Predicting text coherence by treebased modelling of linguistic features
Galletti, Martina
;Gravino, Pietro
;
2023
Abstract
Automatic text coherence modelling plays a crucial role in natural language processing tasks, such as machine translation, summarisation, and question answering. Moreover, text coherence is fundamental to reading comprehension and readers’ engagement, essential to a number of application domains. In this report, we report progress for the Assessing Discourse Coherence in Italian Texts task from EVALITA-23, whose goal is to address automatic coherence detection. The task was challenged by extracting linguistic features used to train a machine learning classifier, leading to minor improvement over the baseline. The feature importance anaI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
