Semantic analysis system for interpreting linguistic structures output by a natural language linguistic analysis system

• US 7,464,026 B2
• Filed: 12/19/2006
• Issued: 12/09/2008
• Est. Priority Date: 01/14/2002
• Status: Expired due to Fees

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Zhao, Lei, Azzam, Saliha, Calcagno, Michael V., Barklund, Par Jonas, Knoll, Sonja S., Chang, Su
• Primary Examiner(s): Hudspeth; David R
• Assistant Examiner(s): Sked; Matthew J.
• Application Number:
  US11/641,251
• Publication Number:
  US 20070100604A1
• Time in Patent Office: 721 Days
• Field of Search: None
• US Class Current: 704/9
• CPC Class Codes: G06F 40/35 Discourse or dialogue representation

Abstract

The present invention is a system and method for performing semantic analysis that interprets a linguistic structure output by a natural language linguistic analysis system. The semantic analysis system converts the linguistic output by the natural language linguistic analysis system into a data structure model referred to as a semantic discourse representation structure (SemDRS).

Claims

1. A method of interpreting a linguistic representation of a textual input, comprising:

receiving a linguistic discourse representation structure (DRS) as the linguistic representation of the textual input;

receiving an entity-and-relation model of a non-linguistic domain;

generating a semantic discourse representation structure (SemDRS) in terms of the entity-and-relation model and based on evidence derived from the linguistic DRS;

receiving a set of semantic mapping rules, each rule having a first side that matches DRS segments of a specified form and a second side that specifies at least a partial SemDRS;

applying the set of semantic mapping rules to the linguistic DRS;

identifying applicable semantic mapping rules as rules having first sides that match any segments of the linguistic DRS;

generating patterns associated with the linguistic DRS, the patterns including a plurality of partial SemDRSs corresponding to the second sides of the applicable semantic mapping rules; and

combining some of the patterns, consistently with the entity-and-relation model, into a single combined solution pattern.

2. The method of claim 1 wherein the linguistic DRS has elements arranged in a box structure and wherein generating a SemDRS further comprises:

arranging the solution pattern in a box structure based on the box structure of the linguistic DRS.

3. The method of claim 2 and further comprising:

prior to combining some of the patterns, generating at least one initial search state including a set of the patterns, wherein the set of patterns is formed such that the patterns in the set account for every element in the linguistic DRS box structure and such that none of the elements in the linguistic DRS box structure is accounted for by more than one pattern in the set of patterns.

4. The method of claim 3 wherein combining some of the patterns comprises:

selecting an initial search state; and

combining all patterns in the selected initial search state into one combined pattern consistently with the entity-and-relation model.

5. The method of claim 4 wherein generating a SemDRS comprises:

for each pattern, generating a pat2drselems mapping between elements in the linguistic DRS and the patterns based on the element of the linguistic DRS represented by the first side of the applicable semantic mapping rule that spawned the pattern, and wherein generating at least one initial search state includes accessing the pat2drselems mapping.

6. The method of claim 5 wherein generating at least one initial search state comprises:

identifying a set of preferences corresponding to the set of patterns, the preferences being indicative of how the patterns are to be combined to obtain the solution pattern.

7. The method of claim 6 and further comprising:

generating the set of preferences.

8. The method of claim 7 wherein generating patterns comprises:

generating a set of semantic entities or semantic relations, each relation having an associated source entity and a destination entity;

loosening the patterns to obtain loosened patterns by replacing at least some of the source and destination entities in the set of patterns with abstract entities and wherein generating the set of preferences includes generating at least one preference for each loosened pattern indicative of how the loosened pattern is to relate to other patterns.

9. The method of claim 3 wherein generating patterns comprises:

identifying elements in the linguistic DRS that are not associated with an applicable semantic mapping rule; and

generating a semantic entity pattern corresponding to each of the identified elements.

10. The method of claim 9 wherein generating the initial search state comprises:

identifying words in the textual input that have a semantic content represented by the box structure of the linguistic DRS but that are not associated with a pattern; and

generating an ignorable pattern corresponding to each of the identified words.

11. The method of claim 10 and further comprising:

receiving a list of tokens in the textual input;

maintaining a mapping of the tokens to the elements of the linguistic DRS; and

maintaining a mapping between elements of the linguistic DRS and the patterns generated.

12. The method of claim 10 wherein generating a SemDRS further comprises:

identifying tokens that have a semantic content represented by the box structure of the linguistic DRS;

applying string-based rewrite rules to the identified tokens; and

generating additional patterns based on application of the string-based rewrite rules.

13. The method of claim 1 wherein generating a SemDRS comprises:

generating a plurality of SemDRSs ranked in order of cost.

14. A semantic analysis system, comprising:

a controller configured to receive a linguistic discourse representation structure (DRS) as a linguistic representation of a textual input, an entity-and-relation model of a non-linguistic domain, and a set of semantic mapping rules;

an interpretation fragment generator, coupled to the controller, configured to apply the semantic mapping rules to the linguistic DRS to generate semantic interpretation fragments, wherein each of the semantic mapping rules has a first side that matches DRS segments of a specified form and a second side that specifies at least a partial SemDRS; and

an interpretation assembly component, coupled to the controller, receiving the semantic interpretation fragments and generating at least one solution pattern from the semantic interpretation fragments, the controller generating a semantic discourse representation structure (SemDRS) from the solution patterns consistent with the entity-and-relation model, wherein the interpretation assembly component generates the solution pattern by combining some of the interpretation fragments, consistently with the entity-and-relation model, into a single combined solution pattern.

15. The semantic analysis system of claim 14 wherein the linguistic DRS has elements arranged in a box structure and wherein the controller is configured to generate the SemDRS by arranging the solution pattern in a box structure based on the box structure of the linguistic DRS.