Natural Language Data Queries on Multiple Heterogenous Data Sources

Abstract

Motivated by a real-world scenario, we enable end users to query data due natural language from different sources like spreadsheets and databases. We provide a natural language user interface (NLUI) solution on how real-world entities and relations between them can be interpreted as a model to allow end user questions on the data. Therefore, the system enables end users to give instructions step-by-step, to avoid the complexity in full descriptions and give directly feedback of success. An evaluation is conducted with human users who had to perform a series of tasks using natural language. Overall, 13 end user took part in our survey with ten questions. 94.9% of all answers in the first part could be resolved on spreadsheet data, and 62,5% on SQL database.