Linguistic Descriptions for Automatic Generation of Textual Short-Term Weather Forecasts on Real Prediction Data
TABLE I: Polishing stage questionnaire score
['Questions', 'Average score', 'Standard deviation']
One expert meteorologist answered the proposed questionnaire for the initial 45 automatically generated forecasts. In this sense, the expert identified the content and language of the generated forecasts with the ones he would provide in a high degree. However, from each individual question score we could extract additional conclusions which, in general, implied that there was room for improvement, especially on Question 4 and on some variables from Question 1 and 2. This was due to several repetitive sentences produced by the NLG stage in some of the variables (especially precipitation) and to some expressions which were not appropriate for some variables.