Open information extraction based on lexical semantics

Abstract

Background: Open Information Extraction (Open IE) aims to obtain not predefined, domain-independent relations from text. This article introduces the Open IE research field, thoroughly discussing the main ideas and systems in the area as well as its main challenges and open issues. The paper describes an open extractor elaborated from the belief that it is not necessary to have an enormous list of patterns or several types of linguistic labels to better perform Open IE. The extractor is based on generic patterns that identify relations not previously specified, including rules corresponding to Cimiano and Wenderoth proposal to learn Qualia structure. Methods: Named LSOE (Lexical-Syntactic pattern-based Open Extractor) and designed to validate such strategy, this extractor is presented and its performance is compared with two Open IE systems. Results: The results demonstrate that LSOE extracts relations that are not learned by other extractors and achieves compatible precision. Conclusions: The work reported here contributes with a new Open IE approach based on pattern matching, demonstrating the feasibility of an extractor based on simple lexical-syntactic patterns.