We propose a generation task for Italian -more specifically, a style transfer task for headlines of Italian newspapers. This is the first shared task on generation included in the EVALITA evaluation framework. Indeed, one of the reasons to have this task is to stimulate more research on generation within the Italian community. With this aim in mind, we release to the participating teams not only training data, but also a baseline sequence to sequence model that performs the task in order to help everyone get started, even when not accustomed to Natural Language Generation (NLG) approaches. Contextually, we explore the complex issue of automatic evaluation of generated text, which is receiving particular attention in the NLG community.

CHANGE-IT@EVALITA 2020:Change Headlines, Adapt News, GEnerate

Felice Dell'Orletta;
2020

Abstract

We propose a generation task for Italian -more specifically, a style transfer task for headlines of Italian newspapers. This is the first shared task on generation included in the EVALITA evaluation framework. Indeed, one of the reasons to have this task is to stimulate more research on generation within the Italian community. With this aim in mind, we release to the participating teams not only training data, but also a baseline sequence to sequence model that performs the task in order to help everyone get started, even when not accustomed to Natural Language Generation (NLG) approaches. Contextually, we explore the complex issue of automatic evaluation of generated text, which is receiving particular attention in the NLG community.
2020
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Natural Language Generation
Style transfer
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/400923
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