Rebuilding the Story of a Hero: Information Extraction in Ancient Argentinian Texts

Abstract

Large amounts of ancient documents have become available in the last years, regarding Argentinian history. This fact turns possible to find interesting and useful aggregated information. This work proposes the application of Natural Language Processing, Text Mining and Visualization tools over Argentinian ancient document repositories. Conceptual maps and entity networks make up the first target of this preliminary paper. The first step is the normalization of OCR acquired books of General G¨uemes. Exploratory analyses reveal the presence of manifold spelling errors, due to the OCR acquisition process of the volumes. We propose smart automatic ways for overcoming this issue in the process of normalization. Besides, a first topic landscape of a subset of volumes is obtained and analysed, via Topic Modelling tools.