Extraction of geographic entities from biological textual sources

Abstract

This work is focused on the exploration and application of entities extraction techniques for the codification and identification of geographical locations present in the geographic distribution section within botanic documents, such as the plant species manual of Costa Rica. Several technologies must be combined to achieve such objective, among them is Natural Language Processing (NLP) that helps in the extraction of entities with the usage of gazetteers. Another technology is the usage of rules (regular expressions, Deterministic Automata, context-free grammars). Additional to the identification and codification, an algorithm to bind the place names extracted to authorized sources such as gazetteer is presented. This algorithm identifies and enriches the entry text with extra information, extracted from the paragraphs where the distribution is defined in a semi unstructured text. The values of interest for this work are: world and Costa Rica distribution. After those values are identified, the information can be processed and become useful for diverse applications, such as geographic information systems. Other research projects might be interested in the results of this project. The evaluation consists in manually judging randomly selected sample of the results to establish if the algorithm yields useful data. The judgment features the evaluation of the world and Costa Rica distribution using the source context, given 3 possible values: GOOD, BAD, UNKNOWN. The ideal is to have the least BAD percentage. The algorithm is relatively good to geo-code and bind the world distribution. More work needs to be done for the Costa Rica distribution.