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.
This research work has been supported by the CICYT project TIN2013-46238-C4-4-R, and DGA-FSE. Our gratitude to Dr. Eduardo Mena and AEMET.
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Notes
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For clarity’s sake, we show the examples translated to English.
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FP85 is the tag used by AEMET to indicate that this is a two-day weather forecast.
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Galicia is a Spanish region.
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The system returns a N/A (Not Applicable) value when there is no possibility of performing the verification process. For example, frosts: there are no observational data related to frost.
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This means that if it is said in the weather prediction temperature values remain unchanged, verification values will be actually valid between 2 degrees up or down.
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Garrido, A.L., Buey, M.G., Muñoz, G., Casado-Rubio, JL. (2016). Information Extraction on Weather Forecasts with Semantic Technologies. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science(), vol 9612. Springer, Cham. https://doi.org/10.1007/978-3-319-41754-7_12
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