Combining Information Extraction and Text Segmentation methods in Greek Texts

Abstract

In this paper we examine the benefit of performing named entity recognition (NER) and co-reference resolution to a Greek corpus used for text segmentation. The aim here is to examine whether the combination of text segmentation and information extraction is beneficial for identifying various topics that appear in a document. NER was performed using an already existing tool for the Greek corpus. Produced annotations were manually corrected and enriched to cover four types of named entities. Co-reference resolution was subsequently performed manually. The evaluation, using four text segmentation algorithms leads to the conclusion that, information extraction techniques appear to be a promising solution in capturing semantic information for segmentation purposes.