Natural Language Querying System Through Entity Enrichment
Amavi, Joshua, Ferrari, Mirian Halfeld, Hiot, Nicolas
–arXiv.org Artificial Intelligence
This paper focuses on a domain expert querying system over databases. It presents a solution designed for a French enterprise interested in offering a natural language interface for its clients. The approach, based on entity enrichment, aims at translating natural language queries into database queries. In this paper, the database is treated through a logical paradigm, suggesting the adaptability of our approach to different database models. The good precision of our method is shown through some preliminary experiments.
arXiv.org Artificial Intelligence
Oct-21-2024
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- Lisbon (0.04)
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- Île-de-France > Paris
- Paris (0.04)
- Centre-Val de Loire > Loiret
- Orleans (0.04)
- Île-de-France > Paris
- Portugal > Lisbon
- North America > United States
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