Every type of text, whether written or spoken, contains information and meaning. If for us as humans the production and comprehension of words, sentences and texts is something natural, the same is not true for computers. The reason for this is that the information coming from this type of data is often in an unstructured format, i.e. lacking a basic organisational and interpretative scheme, something that machines love so much.

Natural Language Processing is that branch of Artificial Intelligence that helps computers bridge the language gap, enabling comprehension and generation of written and spoken text.

NLP techniques structure and prepare language so that the information it contains can be understood, interpreted and organised by machines. Some NLP targets are topic classification, Sentiment Analysis, Named Entity Recognition and Document Search.

It is thanks to Natural Language Processing that we are able to conduct large-scale textual analyses in a short time, automate repetitive procedures and extract knowledge from documents, audio and video files in order to catalogue them on the basis of recognised metadata.