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Identifying Relevant Sentences in News Articles for Event Information Extraction

RIM FAIZ

LARODEC, IHEC of Carthage, 2016 Carthage-Presidence, Tunisia

https://doi.org/10.1142/S0219427906001384Cited by:5 (Source: Crossref)

Abstract

This paper develops a Natural Language Processing method for extracting temporal information of events from news articles. The extraction process is based on the result of a morpho-syntactic analysis. The obtained results, which are a translation of morpho-syntactic sentences, are skimmed in order to identify temporal markers.

In our approach, we consider a specific description of events. Our approach is based on a methodology of temporal markers classes and on a contextual exploration method.

Our experimental results indicate that our approach is significant for extracting relevant event information. We have also achieved a system, called EXEV, on the basis of the proposed approach and have empirically verified its effectiveness. More specifically, EXEV system automatically extracts all information about events (paragraphs or sentences) from news articles and specifies more information about events: associations, locations, temporal settings, etc.

The system was tested on press articles and gives recall and precision more than 80%.

Keywords:

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