System for semantic interpretation

• US 9,659,005 B2
• Filed: 12/19/2014
• Issued: 05/23/2017
• Est. Priority Date: 05/16/2014
• Status: Expired due to Fees

• Current Assignee: Semantix Technologies Corporation
• Original Assignee: Semantix Technologies Corporation
• Inventors: Ramish, John
• Primary Examiner(s): Zhu, Richard
• Application Number:
  US14/577,642
• Publication Number:
  US 20150331850A1
• Time in Patent Office: 886 Days
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/36 Creation of semantic tools, e.g. ontology or thesauri
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 40/151 Transformation
• CPC Class Codes: G06F 40/154 Tree transformation for tree-structured or markup documents, e.g. XSLT, XSL-FO or stylesheets
• CPC Class Codes: G06F 40/20 Natural language analysis semantic analysis of natural language G06F40/30
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30

Abstract

A semantic database is generated to provide answers to questions by users. Text processors can receive text from text sources, and can convert the text into intermediate logical statements. The text processors can then convert these statements into unambiguous semantic representations. A semantic database connected to the text processors can store the semantic representations. Query processors connected to the semantic database can receive a question from a computing device operated by a user, and can convert the question into intermediate logical subqueries. The query processors can then use a disambiguation table to generate unambiguous semantic subqueries from these intermediate logical subqueries. Using the semantic database, the query processors can match each semantic subquery to the stored semantic representation, and join results of the matching as appropriate, to determine one or more answers to the question. The query processors can send the one or more answers to the computing device.

Claims

1. A method comprising:

receiving by one or more text processors, text from one or more text sources;

converting, by the one or more text processors, the text into a plurality of intermediate logical statements that abstract over the syntactic form of information in the text;

converting, by the one or more text processors using a semantic model, each intermediate logical statement into a semantic representation that equates intermediate logical statements having equivalent meanings

such that

the semantic model comprises a plurality of frames, each frame representing a relation or event and comprising one or more variables serving roles in the relation or event and each frame comprising one or more equivalent patterns, each pattern having a form of an intermediate logical statement including at least one variable and comprising a definition of a logical form that corresponds to a plurality of logically equivalent grammatical forms;

sending, by one or more text processors, the semantic representation to a semantic database configured to store the semantic representation;

receiving a query from a computing device;

converting the query, by one or more query processors, connected to the semantic database into one or more semantic subqueries;

matching, by the semantic database, each semantic subquery to stored semantic representations and joining results as appropriate to determine one or more answers to the query;

sending, by the one or more query processors, the one or more answers to the computing device from which the query was received.

2. The method of claim 1, wherein the text comprises a plurality of sentences.

3. The method of claim 1, wherein the one or more text sources comprise at least one of:

web pages and internal documents.

4. The method of claim 1, wherein each intermediate logical statement corresponds to a tree having a root node, one or more other nodes, and one or more edges, the root node representing a verb in the intermediate logical statement, the one or more other nodes representing at least one of a logical subject, a logical object, prepositional objects, and other modifiers in the intermediate logical statement, and the one or more edges identifying relationships among the root and the one or more other nodes.

5. The method of claim 1, wherein each frame comprises constraints on types of the variables.

6. The method of claim 1, wherein the plurality of frames are hierarchically organized as at least one child frame and at least one parent frame, the at least one child frame expressing a meaning that is narrower than a meaning of the at least one parent frame, the at least one child frame logically implying the at least one parent frame.

7. The method of claim 6, wherein the at least one child frame permits specialization that allows facts in the at least one parent frame to be narrowed in meaning so as to belong to the at least one child frame.

8. The method of claim 1, wherein at least one frame is related to at least one other frame with a lateral implication such that facts in the at least one other frame are inferred non-hierarchically from facts in the at least one frame.

9. The method of claim 1, wherein the semantic model is generated using at least one processor, the generation of the semantic model comprising:

receiving one or more intermediate logical statements that abstract over the syntactic form of the information in the text;

substituting variables for nouns in the one or more intermediate logical statements to generate corresponding patterns;

exploiting coreference information about nouns to obtain candidate semantic links between the corresponding patterns;

clustering the linked patterns based on a similarity metric; and

generating, based on a review of the clustered patterns, a frame hierarchy comprising a plurality of frames forming the semantic model.

10. The method of claim 9, wherein the at least one processor is the one or more text processors.

11. The method of claim 1, wherein the one or more text processors and the semantic database are connected via a communication network.

12. A method comprising:

receiving by one or more text processors text for one or more text sources;

converting, by one or more text processors, the text into a plurality of intermediate logical statements that abstract over syntactic form of information in the text, wherein the converting of the text into intermediate logical statements of the text by the one or more text processors comprises one or more of,

parsing the text into a parse tree;

extracting and labeling named entities;

resolving entity mentions within and across documents for coreference;

disambiguating word senses, so as to assign sense identifiers to words;

replacing relative pronouns in the parse tree with corresponding referents;

replacing entity mentions including pronouns and definite nominal in the parse tree with canonical mentions;

identifying intermediate logical statements from at least one of verbs, verbals, appositives, event nouns, possessives, and special constructs in the parse tree;

identifying for each intermediate logical statement the corresponding logical subjects, logical objects, prepositional phrases, and other modifiers from the parse tree;

converting possessives from the parse tree into prepositional forms;

converting indirect objects from the parse tree into prepositional forms; and

distributing over conjunctions in the parse tree; and

sub-substituting variables for subordinate clauses in the parse tree;

converting, by the one or more text processors using a semantic model, each intermediate logical statement into a semantic representation that equates logical statements having equivalent meanings;

sending, by one or more text processors, the semantic representation to a semantic database configured to store the semantic representation;

receiving a query from a computing device;

converting the query, by one or more query processors, connected to the semantic database into one or more semantic subqueries;

matching, by the semantic database, each semantic subquery to stored semantic representations and joining results as appropriate to determine one or more answers to the query; and

sending, by the one or more query processors, the one or more answers to the computing device from which the query was received.

13. A method comprising:

receiving by one or more text processors, text from one or more text sources;

converting, by the one or more text processors, the text into a plurality of intermediate logical statements that abstract over the syntactic form of information in the text;

converting, by the one or more text processors using a semantic model, each intermediate logical statement into a semantic representation that equates intermediate logical statements having equivalent meanings

such that

the semantic model comprises a plurality of frames, each frame representing a relation or event and comprising one or more variables serving roles in the relation or event and each frame comprising one or more equivalent patterns, each pattern having a form of an intermediate logical statement including at least one variable and comprising a definition of a logical form that corresponds to a plurality of logically equivalent grammatical forms;

sending, by one or more text processors, the semantic representation to a semantic database configured to store the semantic representation;

receiving a query from a computing device;

converting the query, by one or more query processors, connected to the semantic database into one or more semantic subqueries;

matching, by the semantic database, each semantic subquery to stored semantic representations and joining results as appropriate to determine one or more answers to the query;

sending, by the one or more query processors, the one or more answers to the computing device from which the query was received

wherein the conversion of each intermediate logical statement into the semantic representation by the one or more text processors comprises;

receiving the intermediate logical statement;

identifying candidate interpretations associated with the intermediate logical statement, a candidate interpretation being characterized by a frame, bindings for some or all variables of the frame, and possibly supplemental modifiers; and

selecting, from the candidate interpretations, a best interpretation based on at least one of variable type compatibility and likelihood, the best interpretation characterizing the semantic representation;

wherein the conversion of each intermediate logical statement into the semantic representation by the one or more text processors further comprises;

specializing the selected interpretation to a narrower meaning as applicable based on at least one of variable type compatibility and likelihood;

deducing any applicable lateral implications from the specialized interpretation; and

recursively specializing and deducing lateral implications for each new fact concluded from a lateral implication in order to generate the semantic representation.

14. A method comprising:

receiving by one or more text processors, text from one or more text sources;

converting, by the one or more text processors, the text into a plurality of intermediate logical statements that abstract over the syntactic form of information in the text;

converting, by the one or more text processors using a semantic model, each intermediate logical statement into a semantic representation that equates intermediate logical statements having equivalent meanings

such that

the semantic model comprises a plurality of frames, each frame representing a relation or event and comprising one or more variables serving roles in the relation or event and each frame comprising one or more equivalent patterns, each pattern having a form of an intermediate logical statement including at least one variable and comprising a definition of a logical form that corresponds to a plurality of logically equivalent grammatical forms;

sending, by one or more text processors, the semantic representation to a semantic database configured to store the semantic representation;

receiving a query from a computing device;

converting the query, by one or more query processors, connected to the semantic database into one or more semantic subqueries;

matching, by the semantic database, each semantic subquery to stored semantic representations and joining results as appropriate to determine one or more answers to the query;

sending, by the one or more query processors, the one or more answers to the computing device from which the query was received;

wherein the conversion of each intermediate logical statement into the semantic representation by the one or more text processors comprises;

receiving the intermediate logical statement;

identifying candidate interpretations associated with the intermediate logical statement, a candidate interpretation being characterized by a frame, bindings for some or all variables of the frame, and possibly supplemental modifiers; and

selecting, from the candidate interpretations, a best interpretation based on at least one of variable type compatibility and likelihood, the best interpretation characterizing the semantic representation;

wherein identifying the candidate interpretations by the one or more text processors comprises;

identifying matching pattern forms, a pattern form of the matching pattern forms being a pattern with wildcard characters in place of variables to indicate that the variables are undistinguished;

selecting, from the identified pattern forms, a pattern form that binds to the most elements of the intermediate logical statement and is maximally specific to the intermediate logical statement;

identifying patterns in frames that match the selected pattern form; and

determining interpretations given by each matching pattern, the determined interpretations being the candidate interpretations.

15. A method comprising:

receiving, by one or more query processors, a question from a computing device;

converting, by one or more query processors, the question into one or more intermediate logical subqueries that abstract over the syntactic form of the question;

wherein the conversion of the question into the intermediate logical subqueries by the one or more query processors comprises one or more of;

parsing the question into a parse tree;

converting the parse tree into a declarative form;

identifying explicit and implicit query variables in the parse tree;

replacing relative pronouns in the parse tree with corresponding referents;

replacing entity mentions including pronouns and definite nominals in the parse tree statements with canonical mentions;

identifying intermediate logical subqueries from at least one of verbs, verbals, appositives, event nouns, possessives, and special constructs in the parse tree;

identifying, for each intermediate logical subquery, corresponding logical subjects, logical objects, prepositional phrases, and other modifiers from the parse tree;

converting possessives from the parse tree into prepositional forms;

converting indirect objects from the parse tree into prepositional forms; and

distributing over conjunctions in the parse tree; and

substituting variables for subordinate clauses in the parse tree;

converting, by the one or more query processors, each intermediate logical subquery into a semantic subquery in a representation that equates intermediate logical subqueries having equivalent meanings;

sending, by one or more query processors, the semantic query to the database, the semantic query being one or more semantic subqueries joined together;

retrieving, by one or more database processors, facts from the database that match the semantic subqueries;

joining, by one or more database processors, the facts when necessary to generate one or more answers to the question;

returning by one or more database processors, the joined facts to the one or more query processors; and

sending, by one or more query processors, the one or more answers to the computing device.

16. The method of claim 15, further comprising:

combining, filtering, and reorganizing the one or more answers before sending the one or more answers to the computing device.

17. The method of claim 15, wherein the computing device executes a graphical user interface that displays the one or more answers to the question.

18. The method of claim 15, wherein each intermediate logical subquery corresponds to a tree having a root node, one or more other nodes, and one or more edges, the root node representing a verb in the intermediate logical subquery, the one or more other nodes representing at least one of a logical subject, a logical object, prepositional objects, and other modifiers in the intermediate logical subquery, and the one or more edges identifying relationships among the root and the one or more other nodes.

19. The method of claim 15, wherein the conversion of the intermediate logical subquery into the semantic subquery by the one or more query processors comprises:

identifying a surface form that corresponds to the intermediate logical subquery;

retrieving interpretations for the surface form from a disambiguation table in the database; and

selecting, from the retrieved interpretations, a highest-scoring interpretation that is compatible with query variables of the intermediate logical subquery, the highest-scoring interpretation characterizing the semantic subquery.

20. The method of claim 19, wherein the disambiguation table is generated by:

identifying patterns for each semantic frame, aliases for each entity, and words for each noun or adjective sense as surface forms;

generating surface forms for each interpreted semantic fact by combining the surface forms for the semantic frame of the fact with the surface forms of one or more frame elements; and

assigning scores to interpretations for each surface form.

21. The method of claim 20, wherein the scores for interpretations are computed as frequencies of the interpretations.

22. The method of claim 20, wherein:

the scores are proportional to P(surface_form|interpretation)*P(interpretation), the scores being computed as frequencies of the interpretations weighted by the probability of generating the surface form given the interpretation.

23. The method of claim 15, wherein the one or more query processors and the semantic database are connected via a communication network.

24. A system comprising:

one or more text processors receiving text from one or more text sources, the one or more text processors converting the text into intermediate logical statements that abstract over syntactic form, the one or more text processors converting each intermediate logical statement into a semantic representation that equates intermediate logical statements having equivalent meanings;

a semantic database connected to the one or more text processors, the semantic database receiving the semantic representation from the one or more text processors, the semantic database storing the semantic representation;

one or more query processors connected to the semantic database, the one or more query processors receiving a question from a computing device, the one or more query processors converting the question into one or more intermediate logical subqueries that abstract over syntactic form, the one or more query processors converting each intermediate logical subquery into a semantic subquery in a representation that equates intermediate logical subqueries having equivalent meanings, wherein the converting into a semantic subquery uses a semantic model that comprises a plurality of frames, each frame representing a relation or event and comprising one or more variables serving roles in the relation or event and each frame comprising one or more equivalent patterns, each pattern having a form of an intermediate statement including at least one variable and comprising a definition of a logical form that corresponds to a plurality of logically equivalent grammatical forms, the semantic database matching each semantic subquery to the stored semantic representations and joining results as appropriate to determine one or more answers to the question, the one or more query processors sending the one or more answers to the computing device that outputs the one or more answers.

25. A system comprising:

one or more text processors receiving text from one or more text sources, the one or more text processors converting the text into intermediate logical statements that abstract over syntactic form and converting each logical statement into a semantic representation that equates logical statements that have equivalent meanings, wherein the converting into a semantic representation uses a semantic model that comprises a plurality of frames, each frame representing a relation or event and comprising one or more variables serving roles in the relation or event and each frame comprising one or more equivalent patterns, each pattern having a form of an intermediate statement including at least one variable and comprising a definition of a logical form that corresponds to a plurality of logically equivalent grammatical forms;

a semantic database connected to the one or more text processors and receiving and storing the semantic representation; and

one or more query processors connected to the semantic database, the one or more query processors receiving a query from a computing device and converting the query into one or more semantic subqueries,

wherein the semantic database matches each semantic subquery to stored semantic representations and joins results to determine one or more answers to the query, the one or more query processors sending the determined one or more answers to the computing device.

26. The system of claim 25, wherein:

the one or more query processors use the semantic model to convert the question to the semantic query.

27. The system of claim 26, wherein:

the one or more text processors and the semantic database are connected via a first communication network; and

the one or more query processors and the semantic database are connected via a second communication network.

28. The system of claim 27, wherein the first communication network is same as the second communication network.

29. The system of claim 27, wherein the first communication network is different from the second communication network.