Abstract: In various embodiments, methods and systems for language scaling a natural language processing system (NLPS) are provided. A database schema of a database is accessed. The database schema includes entities that are defined in a query natural language different from an NLPS natural language upon which NLPS components are built. The entities are communicated to a machine translation service and top translations. A translated database schema model is generated based on the entities and translations. When a query associated with the query natural language and the database schema is received, a query translation is generated. The query translation comprises selectively translated portions of the query based on a selective translation mechanism that includes accessing the machine translation service to translate selected portions of the query. The selected portions are selected based on the translated database schema. The query translation is executed on the NLPS components to identify query results.

Abstract: In various embodiments, methods and systems for language scaling a natural language processing system (NLPS) are provided. A database schema of a database is accessed. The database schema includes entities that are defined in a query natural language different from an NLPS natural language upon which NLPS components are built. The entities are communicated to a machine translation service and top translations. A translated database schema model is generated based on the entities and translations. When a query associated with the query natural language and the database schema is received, a query translation is generated. The query translation comprises selectively translated portions of the query based on a selective translation mechanism that includes accessing the machine translation service to translate selected portions of the query. The selected portions are selected based on the translated database schema. The query translation is executed on the NLPS components to identify query results.