IP Library Granted Patent US 10,706,369
Granted Patent B2
US 10,706,369 · App. 15/419,078 · Granted Jul 7, 2020

Verification of information object attributes

Inventors: Anna Pospelova (Moscow, RU); Elmira Rakhmatulina (Saratov, RU)
Assignee: ABBYY Production LLC
G06N20/00G06F16/313G06F40/268G06F40/284G06F40/289G06F40/30
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Quick Facts
Patent No.
US 10,706,369
App. No.
15/419,078
Granted
Jul 7, 2020
Kind
B2
Abstract

Systems and methods for utilizing user-verified data for training confidence level models. An example method comprises: receiving a first attribute value and a second attribute value associated with an information object representing an entity referenced by a natural language text; receiving a first confidence level associated with the first attribute value and a second confidence level associated with the second attribute value; responsive to determining that the first confidence level falls below a threshold confidence value, displaying the first attribute value using a verification graphical user interface; responsive to receiving, via the verification graphical user interface, a first input verifying the first attribute value, performing at least one of: increasing the first confidence level by a first pre-defined value or setting the first confidence level to a second pre-defined value; displaying the second attribute value using the verification graphical user interface; and responsive to failing to receive, before a triggering event, via the verification graphical user interface, a second input verifying the second attribute value, performing at least one of: increasing the second confidence level by a third pre-defined value or setting the second confidence level to a fourth pre-defined value, wherein the third pre-defined value is less than the first pre-defined value and the fourth pre-defined value is less than the second pre-defined value.

Claims (47)

1. A method, comprising:

receiving, by a processing device, a first attribute value and a second attribute value associated with an information object representing an entity referenced by a natural language text;

evaluating a confidence function to determine a first confidence level associated with the first attribute value and a second confidence level associated with the second attribute value, wherein the confidence function is associated with a set of production rules, wherein the first attribute value and the second attribute value are produced by the set of production rules;

responsive to determining that the first confidence level falls below a threshold confidence value, displaying the first attribute value using a verification graphical user interface;

responsive to receiving, via the verification graphical user interface, a first input confirming the first attribute value, performing at least one of: increasing the first confidence level by a first pre-defined value or setting the first confidence level to a second pre-defined value;

displaying the second attribute value using the verification graphical user interface; and

responsive to failing to receive, before a triggering event, via the verification graphical user interface, a second input verifying the second attribute value, performing at least one of: increasing the second confidence level by a third pre-defined value or setting the second confidence level to a fourth pre-defined value, wherein the third pre-defined value is less than the first pre-defined value and the fourth pre-defined value is less than the second pre-defined value.

2. The method of claim 1 , wherein the triggering event is provided by expiration of a certain timeout that has been initialized by displaying the second attribute value.

3. The method of claim 1 , wherein the triggering event is provided by receiving a third user input causing the verification graphical user interface to cease displaying the second attribute value.

4. The method of claim 1 , wherein the triggering event is provided by receiving, after displaying the second attribute value, a fourth user input causing the verification graphical user interface to terminate.

5. The method of claim 1 , further comprising:

appending, to a training data set, at least part of the natural language text referencing the information object, the first attribute value, and the first confidence level.

6. The method of claim 5 , further comprising:

determining, using the training data set, at least one parameter of the confidence function.

7. The method of claim 1 , wherein receiving the attribute value further comprises:

interpreting, using a set of production rules, a plurality of semantic structures to extract a plurality of information objects representing entities referenced by the natural language text.

8. The method of claim 1 , wherein the first input verifying the first attribute value confirms the first attribute value.

9. The method of claim 1 , wherein the first input verifying the first attribute value modifies the first attribute value.

10. A system, comprising:

a memory;

a processor, coupled to the memory, the processor configured to:

receive a first attribute value and a second attribute value associated with an information object representing an entity referenced by a natural language text;

evaluate a confidence function to determine a first confidence level associated with the first attribute value and a second confidence level associated with the second attribute value, wherein the confidence function is associated with a set of production rules, wherein the first attribute value and the second attribute value are produced by the set of production rules;

responsive to determining that the first confidence level falls below a threshold confidence value, display the first attribute value using a verification graphical user interface;

responsive to receiving, via the verification graphical user interface, a first input confirming the first attribute value, perform at least one of: increasing the first confidence level by a first pre-defined value or setting the first confidence level to a second pre-defined value;

display the second attribute value using the verification graphical user interface; and

responsive to failing to receive, before a triggering event, via the verification graphical user interface, a second input verifying the second attribute value, perform at least one of: increasing the second confidence level by a third pre-defined value or setting the second confidence level to a fourth pre-defined value, wherein the third pre-defined value is less than the first pre-defined value and the fourth pre-defined value is less than the second pre-defined value.

11. The system of claim 10 , wherein the processor is further configured to:

appending, to a training data set, at least part of the natural language text referencing the information object, the first attribute value, and the first confidence level.

12. The method of claim 11 , wherein the processor is further configured to:

determining, using the training data set, at least one parameter of the confidence function.

13. The system of claim 10 , wherein receiving the attribute value further comprises:

interpreting, using a set of production rules, a plurality of semantic structures to extract a plurality of information objects representing entities referenced by the natural language text.

14. The system of claim 10 , wherein the triggering event is provided by one of: expiration of a certain timeout that has been initialized by displaying the second attribute value, receiving a third user input causing the verification graphical user interface to cease displaying the second attribute value, or receiving, after displaying the second attribute value, a fourth user input causing the verification graphical user interface to terminate.

15. A computer-readable non-transitory storage medium comprising executable instructions that, when executed by a computer system, cause the computer system to:

receive a first attribute value and a second attribute value associated with an information object representing an entity referenced by a natural language text;

evaluate a confidence function to determine a first confidence level associated with the first attribute value and a second confidence level associated with the second attribute value, wherein the confidence function is associated with a set of production rules, wherein the first attribute value and the second attribute value are produced by the set of production rules;

responsive to determining that the first confidence level falls below a threshold confidence value, display the first attribute value using a verification graphical user interface;

responsive to receiving, via the verification graphical user interface, a first input confirming the first attribute value, perform at least one of: increasing the first confidence level by a first pre-defined value or setting the first confidence level to a second pre-defined value;

display the second attribute value using the verification graphical user interface; and

responsive to failing to receive, before a triggering event, via the verification graphical user interface, a second input verifying the second attribute value, perform at least one of: increasing the second confidence level by a third pre-defined value or setting the second confidence level to a fourth pre-defined value, wherein the third pre-defined value is less than the first pre-defined value and the fourth pre-defined value is less than the second pre-defined value.

16. The computer-readable non-transitory storage medium of claim 15 , further comprising causing the computer system to:

append, to a training data set, at least part of the natural language text referencing the information object, the first attribute value, and the first confidence level.

17. The computer-readable non-transitory storage medium of claim 16 , further comprising executable instructions causing the computer system to:

determine, using the training data set, at least one parameter of the first confidence function.

18. The computer-readable non-transitory storage medium of claim 16 , wherein receiving the attribute value further comprises:

interpreting, using a set of production rules, a plurality of semantic structures to extract a plurality of information objects representing entities referenced by the natural language text.

Assignments (5)
SECURITY INTEREST Recorded Aug 14, 2023
From: ABBYY INC.; ABBYY USA SOFTWARE HOUSE INC.; ABBYY DEVELOPMENT INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS AGENT
Reel/Frame 064730/0964 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 25, 2022
From: ABBYY PRODUCTION LLC
To: ABBYY DEVELOPMENT INC.
Reel/Frame 059249/0873 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 21, 2017
From: POSPELOVA, ANNA; RAKHMATULINA, ELMIRA
To: ABBY PRODUCTION LLC
Reel/Frame 044464/0933 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNOR DOC. DATE PREVIOUSLY RECORDED AT REEL: 042706 FRAME: 0279. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Aug 25, 2017
From: ABBYY INFOPOISK LLC
To: ABBYY PRODUCTION LLC
Reel/Frame 043676/0232 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 6, 2017
From: ABBYY INFOPOISK LLC
To: ABBYY PRODUCTION LLC
Reel/Frame 042706/0279 →