Claims:WE CLAIM
1. A method of performing verifiable query on semantic data, the method comprising:
rendering, via a processor, a visualization of an ontology of the semantic data;
acquiring, via the processor, one or more user interactions with the visualization;
generating, via the processor, a semantic query and a natural language interpretation based on the one or more user interactions; and
presenting, via the processor, the semantic query and the natural language interpretation to a user for validation.

2. The method of claim 1, wherein rendering the visualization further comprises:
receiving a concept of interest in the ontology from the user; and
rendering a segmented view of the ontology based on the concept of interest.

3. The method of claim 1, wherein acquiring the one or more user interactions comprises, for each interaction:
receiving an action performed by the user in the visualization; and
processing the action performed by the user.

4. The method of claim 3, wherein the action comprises at least one of clicking on a data property node, clicking on an object property node, clicking on a super-class node, clicking on a sub-class node, and deleting a sub-clause of the natural language interpretation.

5. The method of claim 1, wherein generating the semantic query comprises:
referring to a semantic query syntax database; and
mapping the one or more user interactions into a syntactically valid semantic query structure.

6. The method of claim 1, wherein generating the natural language interpretation comprises generating the natural language interpretation from the one or more user interactions by employing natural language generation algorithm.

7. The method of claim 1, wherein generating the natural language interpretation comprises generating the natural language interpretation from the semantic query.

8. The method of claim 1, further comprising:
capturing a modification performed by the user to the natural language interpretation; and
generating a modified semantic query based on the modification performed.

9. The method of claim 1, wherein the semantic data is in resource description framework (RDF) format and the semantic query is in SPARQL protocol and RDF query language (SPARQL).

10. A system for performing verifiable query on semantic data, the system comprising:
at least one processor; and
a computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
rendering a visualization of an ontology of the semantic data;
acquiring one or more user interactions with the visualization;
generating a semantic query and a natural language interpretation based on the one or more user interactions; and
presenting the semantic query and the natural language interpretation to a user for validation.

11. The system of claim 10, wherein rendering the visualization further comprises:
receiving a concept of interest in the ontology from the user; and
rendering a segmented view of the ontology based on the concept of interest.

12. The system of claim 10, wherein acquiring the one or more user interactions comprises, for each interaction:
receiving an action performed by the user in the visualization; and
processing the action performed by the user,
and wherein the action comprises at least one of clicking on a data property node, clicking on an object property node, clicking on a super-class node, clicking on a sub-class node, and deleting a sub-clause of the natural language interpretation.

13. The system of claim 10, wherein generating the semantic query comprises:
referring to a semantic query syntax database; and
mapping the one or more user interactions into a syntactically valid semantic query structure.

14. The system of claim 10, wherein generating the natural language interpretation comprises:
generating the natural language interpretation from the one or more user interactions by employing natural language generation algorithm; or
generating the natural language interpretation from the semantic query.

15. The system of claim 10, wherein the operations further comprise:
capturing a modification performed by the user to the natural language interpretation; and
generating a modified semantic query based on the modification performed.

16. A non-transitory computer-readable medium storing computer-executable instructions for:
rendering a visualization of an ontology of the semantic data;
acquiring one or more user interactions with the visualization;
generating a semantic query and a natural language interpretation based on the one or more user interactions; and
presenting the semantic query and the natural language interpretation to a user for validation.

17. The non-transitory computer-readable medium of claim 16, wherein instructions for acquiring the one or more user interactions comprises, for each interaction, instructions for:
receiving an action performed by the user in the visualization; and
processing the action performed by the user
and wherein the action comprises at least one of clicking on a data property node, clicking on an object property node, clicking on a super-class node, clicking on a sub-class node, and deleting a sub-clause of the natural language interpretation.

18. The non-transitory computer-readable medium of claim 16, wherein instructions for generating the semantic query comprises instructions for:
referring to a semantic query syntax database; and
mapping the one or more user interactions into a syntactically valid semantic query structure.

19. The non-transitory computer-readable medium of claim 16, wherein instructions for generating the natural language interpretation comprises instructions for:
generating the natural language interpretation from the one or more user interactions by employing natural language generation algorithm; or
generating the natural language interpretation from the semantic query.

20. The non-transitory computer-readable medium of claim 16, further storing instructions for:
capturing a modification performed by the user to the natural language interpretation; and
generating a modified semantic query based on the modification performed.

Dated this 30th day of July, 2015

Swetha S.N
Of K&S Partners
Agent for the Applicant
, Description:TECHNICAL FIELD

This disclosure relates generally to information retrieval and more particularly to a system and method for enabling a user to perform a verifiable query on semantic data.