Information extraction on weather forecasts with semantic technologies

Abstract

In this paper, we describe a natural language application which extracts information from worded weather forecasts with the aim of quantifying the accuracy of weather forecasts. Our system obtains the desired information from the weather predictions taking advantage of the structure and language conventions with the help of a specific ontology. This automatic system is used in verification tasks, it increases productivity and avoids the typical human errors and probable biases in what people may incur when performing this task manually. The proposed implementation uses a framework that allows to address different types of forecasts and meteorological variables with minimal effort. Experimental results with real data are very good, and more important, it is viable to being used in a real environment.