  Extracting patterns and useful information from Natural Language datasets is
a challenging task, especially when dealing with data written in a language
different from English, like Italian. Machine and Deep Learning, together with
Natural Language Processing (NLP) techniques have widely spread and improved
lately, providing a plethora of useful methods to address both Supervised and
Unsupervised problems on textual information. We propose RECKONition, a
NLP-based system for Industrial Accidents at Work Prevention. RECKONition,
which is meant to provide Natural Language Understanding, Clustering and
Inference, is the result of a joint partnership with the Italian National
Institute for Insurance against Accidents at Work (INAIL). The obtained results
showed the ability to process textual data written in Italian describing
industrial accidents dynamics and consequences.
