Parser for natural language processing

• US 20060095250A1
• Filed: 11/03/2004
• Published: 05/04/2006
• Est. Priority Date: 11/03/2004
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Zhou, Ming, Wu, Tianlei, Chen, John T.
• Granted Patent: US 7,970,600 B2
• Time in Patent Office: Days
• US Class Current: 704/9
• CPC Class Codes: G06F 40/205 Parsing

Abstract

A computer-implemented method for developing a parser is provided. The method includes accessing a corpus of sentences and parsing the sentences to generate a structural description of each sentence. The parser is trained based on the structural description of each sentence.

Claims

1. A computer-implemented method for developing a parser, comprising:

accessing a corpus of sentences;

parsing the sentences to generate a structural description of each sentence using an existing parser; and

training another parser based on the structural description of each sentence.

2. The method of claim 1 and further comprising transforming the structural descriptions to skeleton relations.

3. The method of claim 1 and further comprising extracting noun phrases from the structural descriptions.

4. The method of claim 1 and further comprising extracting verb groups from the structural descriptions.

5. The method of claim 1 and further comprising extracting skeleton relations from the structural descriptions.

6. The method of claim 1 and further comprising using part-of-speech tags to generate the structural descriptions.

7. The method of claim 1 wherein the existing parser is a hand-crafted parser.

8. The method of claim 1 and further comprising generating a maximum entropy model to identify skeleton relations in a sentence.

9. A computer-readable medium having instructions that developing a parser for use in natural language processing, the instructions comprising:

a corpus of sentences;

an existing parser adapted to parse the sentences to generate a structural description of each; and

a training module adapted to train the parser based on the structural description of each sentence.

10. The computer-readable medium of claim 9 wherein the training module is adapted to transform the structural descriptions to skeleton relations.

11. The computer-readable medium of claim 9 wherein the training module is adapted to extract noun phrases from the structural descriptions.

12. The computer-readable medium of claim 9 wherein the training module is adapted to extract verb groups from the structural descriptions.

13. The computer-readable medium of claim 9 wherein the training module is adapted to extract skeleton relations from the structural descriptions.

14. The computer-readable medium of claim 9 wherein the training module is adapted to use part-of-speech tags to generate the structural descriptions.

15. The computer-readable medium of claim 9 wherein the existing parse is a hand-crafted parser.

16. The computer-readable medium of claim 9 wherein the training module utilizes a maximum entropy model to identify skeleton relations in a sentence.