Probabilistic Logic Programming for Natural Language Processing.
Fabrizio Riguzzi, Evelina Lamma, Marco Alberti, Elena Bellodi, Riccardo Zese, Giuseppe Cota · Institutional Research Information System University of Ferrara (University of Ferrara) · 2016
The ambition of Artificial Intelligence is to solve problems without human intervention. Often the problem description is given in human (natural) language. Therefore it is crucial to find an automatic way to understand a text written by a human. The research field concerned with the interactions between computers and natural languages is known under the name of Natural Language Processing (NLP), one of the most studied fields of Artificial Intelligence. In this paper we show that Probabilistic Logic Programming (PLP) is a suitable approach for NLP in various scenarios. For this purpose we use cplint on SWISH, a web application for Probabilistic Logic Programming. cplint on SWISH allows users to perform inference and learning with the framework cplint using just a web browser, with the computation performed on the server.