QUESTION ANSWERING USING ENTITY REFERENCES IN UNSTRUCTURED DATA

• US 20140280114A1
• Filed: 03/15/2013
• Published: 09/18/2014
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Keysar, Dvir, Shmiel, Tomer
• Granted Patent: US 9,477,759 B2
• Time in Patent Office: Days
• US Class Current: 707/730
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results

Abstract

Methods, systems, and computer-readable media are provided for collective reconciliation. In some implementations, a query is received, wherein the query is associated at least in part with a type of entity. One or more search results are generated based at least in part on the query. Previously generated data is retrieved associated with at least one search result of the one or more of search results, the data comprising one or more entity references in the at least one search result corresponding to the type of entity. The one or more entity references are ranked, and an entity result is selected from the one or more entity references based at least in part on the ranking. An answer to the query is provided based at least in part on the entity result.

Claims

1. A computer-implemented method comprising:

receiving a query, wherein the query is associated at least in part with a type of entity;

generating one or more search results based at least in part on the query;

retrieving previously generated data associated with at least one search result of the one or more search results, the previously generated data comprising one or more entity references in the at least one search result corresponding to the type of entity;

ranking the one or more entity references;

selecting an entity result from the one or more entity references based at least in part on the ranking; and

providing an answer to the query based at least in part on the entity result.

2. The method of claim 1, wherein the query is a natural language query.

3. The method of claim 1, wherein the type of the entity is a person type.

4. The method of claim 1, wherein ranking the one or more entity references comprises ranking based on at least one ranking signal.

5. The method of claim 4, wherein the at least one ranking signal comprises a frequency of occurrence of each respective entity reference.

6. The method of claim 4, wherein the at least one ranking signal comprises a topicality score of each respective entity reference.

7. The method of claim 1, wherein the previously generated data comprises unstructured data.

8. A system comprising:

one or more computers configured to perform operations comprising;

receiving a query, wherein the query is associated at least in part with a type of entity;

generating one or more search results based at least in part on the query;

retrieving previously generated data associated with at least one search result of the one or more search results, the previously generated data comprising one or more entity references in the at least one search result corresponding to the type of entity;

ranking the one or more entity references;

selecting an entity result from the one or more entity references based at least in part on the ranking; and

providing an answer to the query based at least in part on the entity result.

9. The system of claim 8, wherein the query is a natural language query.

10. The system of claim 8, wherein the type of the entity is a person type.

11. The system of claim 8, wherein ranking the one or more entity references comprises ranking based on at least one ranking signal.

12. The system of claim 11, wherein the at least one ranking signal comprises a frequency of occurrence of each respective entity reference.

13. The system of claim 11, wherein the at least one ranking signals comprises a topicality score of each respective entity reference.

14. The system of claim 8, wherein the previously generated data comprises unstructured data.

15. A computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

receiving a query, wherein the query is associated at least in part with a type of entity;

generating one or more search results based at least in part on the query;

retrieving previously generated data associated with at least one search result of the one or more search results, the previously generated data comprising one or more entity references in the at least one search result corresponding to the type of entity;

ranking the one or more entity references;

selecting an entity result from the one or more entity references based at least in part on the ranking; and

providing an answer to the query based at least in part on the entity result.

16. The computer-readable medium of claim 15, wherein the query is a natural language query.

17. The computer-readable medium of claim 15, wherein the type of the entity is a person type.

18. The computer-readable medium of claim 15, wherein ranking the one or more entity references comprises ranking based on at least one ranking signal.

19. The computer-readable medium of claim 18, wherein at least one ranking signal comprises a frequency of occurrence of each respective entity reference.

20. The computer-readable medium of claim 18, wherein the at least one ranking signal comprises a topicality score of each respective entity reference.

21. The computer-readable medium of claim 15, wherein the previously generated data comprises unstructured data.