In this work we show an experiment on building an Open Information Extraction system (OIE) for Italian language. We propose a system wholly reliant on linguistic structures and on a small set of verbal behavior patterns defined putting together theoretical linguistic knowledge and corpus-based statistical information. Starting from elementary one-verb sentences, the system identifies elementary tuples and then, all their permutations, preserving the overall well-formedness (grammaticality) and trying to preserve semantic coherence (acceptability). Although the work focuses only on the Italian language, it can be proficiently extended also to other languages, since it is essentially based only on linguistic resources and on a representative corpus for the language under consideration.
When lexicon-grammar meets open information extraction: A computational experiment for Italian sentences
Guarasci Raffaele;Damiano Emanuele;Minutolo Aniello;Esposito Massimo
2019
Abstract
In this work we show an experiment on building an Open Information Extraction system (OIE) for Italian language. We propose a system wholly reliant on linguistic structures and on a small set of verbal behavior patterns defined putting together theoretical linguistic knowledge and corpus-based statistical information. Starting from elementary one-verb sentences, the system identifies elementary tuples and then, all their permutations, preserving the overall well-formedness (grammaticality) and trying to preserve semantic coherence (acceptability). Although the work focuses only on the Italian language, it can be proficiently extended also to other languages, since it is essentially based only on linguistic resources and on a representative corpus for the language under consideration.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.