Abstract: The invention allows end users to obtain immediate, accurate information from structured databases without writing complex database query commands. The invention allows two different, but synchronized, methods of end user information requests: Spoken or typed Natural Language requests, and a Visual Request Specification method. Furthermore, the invention provides a user the means of “teaching the system the correct interpretation” when an information request was misunderstood by the invention's Natural Language Understanding module.

Abstract: The invention allows end users to obtain immediate, accurate information from structured databases without writing complex database query commands. The invention allows two different, but synchronized, methods of end user information requests: Spoken or typed Natural Language requests, and a Visual Request Specification method. Furthermore, the invention provides a user the means of “teaching the system the correct interpretation” when an information request was misunderstood by the invention's Natural Language Understanding module.

Abstract: The invention answers a user's information request, stated in the user's natural language, by dynamically retrieving and merging facts and information from disparate and possibly geographically dispersed databases and presenting a single answer to the user. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. 37 CFR 1.72(b).

Abstract: The invention answers a user's information request, stated in the user's natural language, by dynamically retrieving and merging facts and information from disparate and possibly geographically dispersed databases and presenting a single answer to the user. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. 37 CFR 1.72(b).

Abstract: The invention is natural language database querying (NLDQ), by a) allowing a user to type an information request using phrases stated in a natural language such as English, b) matching the phrases in the request to semantic objects stored in a hierarchy of ontologies, c) automatically converting the matched semantic phrases into the names of synchronized conceptual objects stored in the same taxonomy, d) automatically mapping the conceptual objects to metadata objects in one or more target databases; e) from the mapped metadata objects, generating a database query stated in a database language such as Structured Query Language (SQL), and f) executing the database query against the target database(s).

Abstract: The invention teaches preparing data sources for a natural language query. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. 37 CFR 1.72(b).

Abstract: The invention teaches preparing data sources for a natural language query. It is emphasized that this abstract is provided to comply with the rules requiring an abstract that will allow a searcher or other reader to quickly ascertain the subject matter of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims.