Preparing a data source for a natural language query

• US 20050043940A1
• Filed: 08/20/2004
• Published: 02/24/2005
• Est. Priority Date: 08/20/2003
• Status: Abandoned Application

• Current Assignee: Marvin Elder
• Original Assignee: Marvin Elder
• Inventors: Elder, Marvin
• Application Number:
  US10/923,164
• Publication Number:
  US 20050043940A1
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 16/24522 Translation of natural language queries to structured queries

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.

Claims

1. A method of enabling a target data source to be queried by natural language searching, the method comprising the sequential acts of:

capturing metadata associated with a target data source, the metadata defining a target concept model; and

processing the target concept model to enable database searching through user queries stated in natural language.

2. The method of claim 1 further comprising reporting an answer, the answer extracted from the target data source.

3. The method of claim 2 wherein the target concept model comprises entities, each entity being logically mapped to a table in a target data source, and each entity comprising at least one attribute, each attribute being logically mapped to one column in the table.

4. The method of claim 3 further comprising defining a logical relationship between a pair of entities in the target concept model based on metadata.

5. The method of claim 1 wherein the target concept model is defined as a subject area, the subject area comprising one or more logical views, the logical view comprising at least two entities.

6. The method of claim 3 wherein a pair of entities are linked based upon one of the following relationships:

an ‘

is-a’

logical relationship, a ‘

has-a’

logical relationship, or a ‘

member-of’

logical relationship.

7. The method of claim 3 wherein each concept entity and each concept attribute is assigned a natural language name.

8. The method of claim 1 wherein processing comprises generating a semantic phrase that associates at least two entities, and storing the semantic phrase in a semantic phrase repository.

9. The method of claim 8 wherein a second semantic phrase may be linked as a child phrase to a parent semantic phrase, the parent semantic phrase already existing in a semantic phrase repository.

10. The method of claim 1 wherein processing adds a new concept model layer to an existing concept model repository, and also adds at least one semantic phase to an existing semantic phrase repository, wherein the two repositories are interdependent.

11. The method of claim 10, wherein the two phrase repositories are structured and organized such that a natural language request for information from a target database can be interpreted by a natural language processor and automatically translated into a data query that returns a precise answer to a user.

12. The method of claim 1 further comprising defining a concept object based on conditions that make the concept object unique.

13. The method of claim 1 further comprising defining a new attribute as a logical equivalent of a predefined attribute associated with an entity.