Method and device for extracting causal from natural language sentences for intelligent systems

• US 10,528,669 B2
• Filed: 03/27/2018
• Issued: 01/07/2020
• Est. Priority Date: 03/20/2018
• Status: Active Grant

• Current Assignee: Wipro Limited
• Original Assignee: Wipro Limited
• Inventors: Chatterjee, Arindam, Ballal, Kartik Subodh
• Primary Examiner(s): Gay, Sonia L
• Application Number:
  US15/937,629
• Publication Number:
  US 20190294671A1
• Time in Patent Office: 651 Days
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/268 Morphological analysis
• CPC Class Codes: G06F 40/289 Phrasal analysis, e.g. finite state techniques or chunking
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G10L 25/30 using neural networks

Abstract

A method and device for extracting causal from natural language sentences is disclosed. The method includes determining, by a computing device, a plurality of parameters for each target word in a sentence inputted by a user. The method further includes processing for each target word, by the computing device, an input vector comprising the plurality of parameters for a causal classifier neural network. The method includes identifying, by the computing device, causal tags associated with each target word in the sentence based on processing of associated input vector. The method includes extracting, by the computing device, the causal text from the sentence based on the causal tags associated with each target word in the sentence. The method further includes providing, by the computing device, a response to the sentence inputted by the user based on the causal text extracted for the sentence.

Claims

1. A method for extracting causal from natural language sentences, the method comprising:

determining, by a computing device, a plurality of parameters for each target word in a sentence inputted by a user wherein the plurality of parameters for a target word comprise a Part of Speech (POS) vector associated with the target word comprising a POS tag for the target word and a POS tag for at least two words preceding the target word, a word embedding for the target word, a word embedding for a head word of the target word, and a dependency label for the target word;

processing for each target word, by the computing device, an input vector comprising the plurality of parameters for a causal classifier neural network;

identifying, by the computing device, causal tags associated with each target word in the sentence based on processing of associated input vector;

extracting, by the computing device, the causal text from the sentence based on the causal tags associated with each target word in the sentence; and

providing, by the computing device, a response to the sentence inputted by the user based on the causal text extracted for the sentence.

2. The method of claim 1, wherein the dependency label for the target word indicates relation of the target with the head word in the sentence.

3. The method of claim 1 further comprising training the causal classifier neural network to identify causal tags associated with words within sentences inputted by user.

4. The method of claim 1, wherein the sentence is inputted by the user as at least one of a verbal input and a textual input.

5. The method of claim 4, wherein the sentence comprises a query asked by the user.

6. The method of claim 5, wherein the response comprises at least one an answer to the query and an action corresponding to the query.

7. The method of claim 1, wherein the causal tags comprise Begin Causal tag, Inside Causal tag, and Others tag.

8. The method of claim 7, wherein the identifying the causal tags associated with each target word comprises:

assigning a Begin Causal tag to a word in the sentence marking the beginning of the causal text;

assigning an Inside Causal tag to each word in the causal text succeeding the word marking the beginning of the causal text; and

assigning an Others tag to each remaining word in the sentence.

9. A computing device for extracting causal from natural language sentences, the device comprising:

a processor; and

a memory communicatively coupled to the processor, wherein the memory stores processor instructions, which, on execution, causes the processor to;

determine a plurality of parameters for each target word in a sentence inputted by a user wherein the plurality of parameters for a target word comprise a Part of Speech (POS) vector associated with the target word comprising a POS tag for the target word and a POS tag for at least two words preceding the target word, a word embedding for the target word, a word embedding for a head word of the target word, and a dependency label for the target word;

process for each target word an input vector comprising the plurality of parameters for a causal classifier neural network;

identify causal tags associated with each target word in the sentence based on processing of associated input vector;

extract the causal text from the sentence based on the causal tags associated with each target word in the sentence; and

provide a response to the sentence inputted by the user based on the causal text extracted for the sentence.

10. The computing device of claim 9, wherein the dependency label for the target word indicates relation of the target with the head word in the sentence.

11. The computing device of claim 9, wherein the processor instructions further cause the processor to train the causal classifier neural network to identify causal tags associated with words within sentences inputted by user.

12. The computing device of claim 9, wherein the sentence is inputted by the user as at least one of a verbal input and a textual input.

13. The computing device of claim 12, wherein the sentence comprises a query asked by the user, and wherein the response comprises at least one an answer to the query and an action corresponding to the query.

14. The computing device of claim 9, wherein the causal tags comprise Begin Causal tag, Inside Causal tag, and Others tag.

15. The computing device of claim 9, wherein to identify the causal tags associated with each target word, the processor instructions further cause the processor to:

assign a Begin Causal tag to a word in the sentence marking the beginning of the causal text;

assign an Inside Causal tag to each word in the causal text succeeding the word marking the beginning of the causal text; and

assign an Others tag to each remaining word in the sentence.

16. A non-transitory computer-readable storage medium having stored thereon, a set of computer-executable instructions causing a computer comprising one or more processors to perform steps comprising:

determining a plurality of parameters for each target word in a sentence inputted by a user wherein the plurality of parameters for a target word comprise a Part of Speech (POS) vector associated with the target word comprising a POS tag for the target word and a POS tag for at least two words preceding the target word, a word embedding for the target word, a word embedding for a head word of the target word, and a dependency label for the target word;

processing for each target word an input vector comprising the plurality of parameters for a causal classifier neural network;

identifying causal tags associated with each target word in the sentence based on processing of associated input vector;

extracting the causal text from the sentence based on the causal tags associated with each target word in the sentence; and

providing a response to the sentence inputted by the user based on the causal text extracted for the sentence.