Improving Information Extraction from Wikipedia Texts using Basic English

Improving Information Extraction from Wikipedia Texts using Basic English Teresa Rodr´ıguez-Ferreira, Adri´an Rabad´an, Raquel Herv´as, Alberto D´ıaz Facultad de Inform´atica Universidad Complutense de Madrid teresaro@ucm.es, arabadan@ucm.es, raquelhb@fdi.ucm.es, albertodiaz@fdi.ucm.es Abstract The aim of this paper is to study the effect that the use of Basic English versus common English has on information extraction from online resources. The amount of online information available to the public grows exponentially, and is potentially an excellent resource for information extraction. The problem is that this information often comes in an unstructured format, such as plain text. In order to retrieve knowledge from this type of text, it must first be analysed to find the relevant details, and the nature of the language used can greatly impact the quality of the extracted information. In this paper, we compare triplets that represent definitions or properties of concepts obtained from three online collaborative resources (English Wikipedia, Simple English Wikipedia and Simple English Wiktionary) and study the differences in the results when Basic English is used instead of common English. The results show that resources written in Basic English produce less quantity of triplets, but with higher quality. Keywords: Information Extraction, Triplets, Basic English 1. Introduction Although software applications could theoretically benefit from the huge amount of information in the Web, they usu- ally face the problem of this information appearing in the form of unstructured data like plain text. The possibility of automatically extracting the knowledge underlying this plain text is therefore becoming increasingly important. Information Extraction (IE) is the process of automatically extracting structured data from unstructured texts. There are different ways to represent data extracted from text, such as in the form of graphs or by using triplets in the form (concept1, verb, concept2) to express relations be- tween concepts extracted from the text. Although there are many IE approaches, in this paper we are only interested in unsupervised techniques that are able to extract information from plain text. For this kind of technique, the characteris- tics of the source text from which the information is going to be extracted play an important role in the obtained re- sults. In this paper we will evaluate whether the use of Ba- sic English instead of common English leads to the ex- traction of more accurate data by implementing an ex- periment that compares triplets extracted from the En- glish Wikipedia1, Simple English Wikipedia2 and Simple English Wiktionary3 (from now on referred to as Sim- ple Wikipedia and Simple Wiktionary). Basic English is a simplification of the English Language created by Og- den (1930) which defends that full communication can be achieved by using only 850 English words. In addition to using Basic English, Simple Wikipedia and Simple Wik- tionary also ask users to write in shorter sentences, use ac- tive voice over passive voice and provide guidelines to help users write sentences with simple structures. The triplets used will represent definitions and properties, concepts that establish a unidirectional IS A or IS relation 1http://www.wikipedia.org 2http://simple.wikipedia.org 3http://simple.wiktionary.org with …

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