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.

Probabilistic logic programming for natural language processing

RIGUZZI, Fabrizio;LAMMA, Evelina;ALBERTI, Marco;BELLODI, Elena;ZESE, Riccardo;COTA, Giuseppe
2017

Abstract

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.
2017
Natural language processing; Probabilistic logic programming; Probabilistic logical inference; Computer Science (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2368070
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