System and method for natural language querying

Abstract

A system and method for information retrieval are presented. A natural language query is received from a client computer. The natural language query is analyzed to identify a plurality of terms, and a relationship between a pair of terms in the plurality of terms is determined using a knowledge model. The knowledge model defines a plurality of entities and interrelationships between one or more of the plurality of entities for a knowledge domain. A triple statement is constructed using the relationship between the pair of terms, and a query is executed against a knowledge base using the triple statement to generate a set of results. The knowledge base identifies a plurality of items, each of the plurality of items is associated with at least one annotation identifying at one of the entities in the knowledge model. The set of results are transmitted to the client computer.

What is claimed is: 
     
         1 . An information retrieval system, comprising:
 a knowledge model database configured to store a knowledge model for a knowledge domain, the knowledge model defining a plurality of entities and interrelationships between one or more of the plurality of entities;   a knowledge base identifying a plurality of items, each of the plurality of items being associated with at least one annotation identifying at one of the entities in the knowledge model database; and   a query processing server configured to:
 receive, from a client computer, a natural language query using a computer network, 
 analyze the natural language query to identify a plurality of terms, 
 identify a first entity in the knowledge model database that is related to at least one term in a pair of terms selected from the plurality of terms, 
 construct a triple statement including the pair of terms and the first entity in the knowledge model database, 
 execute a query against the knowledge base using the triple statement to generate a set of results, and 
 transmit, to the client computer, the set of results. 
   
     
     
         2 . The information retrieval system of  claim 1 , wherein the query processing server is configured to:
 analyze the natural language query using named entity recognition.   
     
     
         3 . The information retrieval system of  claim 1 , wherein the knowledge model database is configured as a triplestore. 
     
     
         4 . The information retrieval system of  claim 1 , wherein the query processing server is configured to:
 determine a distance between each term in the pair of terms using the knowledge model database.   
     
     
         5 . The information retrieval system of  claim 4 , wherein the query processing server is configured to, when the distance between each term in the pair of terms is two or greater, discard the pair of terms. 
     
     
         6 . The information retrieval system of  claim 1 , wherein the query processing server is configured to:
 determine a type of each term in the pair of terms, where the type is one of an instance type, a concept type, and a relationship type.   
     
     
         7 . The information retrieval system of  claim 6 , wherein the query processing server is configured to,when the type of each term in the pair of terms is the instance type or the concept type, analyze each of the plurality of the terms to identify a linking term having a type that is the relationship type, where the linking term links the pair of terms in the knowledge model database, include the linking term in the query. 
     
     
         8 . A method for information retrieval, comprising:
 receiving, from a client computer, a natural language query using a computer network;   analyzing the natural language query to identify a plurality of terms;   identifying a first entity in a knowledge model database that is related to at least one term in a pair of terms selected from the plurality of terms, the knowledge model database defining a plurality of entities and interrelationships between one or more of the plurality of entities for a knowledge domain;   constructing a triple statement including the pair of terms and the first entity in the knowledge model database;   executing a query against a knowledge base using the triple statement to generate a set of results, the knowledge base identifying a plurality of items, each of the plurality of items being associated with at least one annotation identifying at one of the entities in the knowledge model database; and   transmitting, to the client computer, the set of results.   
     
     
         9 . The method of  claim 8 , including analyzing the natural language query using named entity recognition. 
     
     
         10 . The method of  claim 8 , wherein the knowledge model database is configured as a triplestore. 
     
     
         11 . The method of  claim 8 , including determining a distance between each term in the pair of terms using the knowledge model database. 
     
     
         12 . The method of  claim 11 , including, when the distance between each term in the pair of terms is two or greater, discarding the pair of terms. 
     
     
         13 . The method of  claim 8 , including determining a type of each term in the pair of terms, where the type is one of an instance type, a concept type, and a relationship type. 
     
     
         14 . The method of  claim 13 , including, when the type of each term in the pair of terms is the instance type or the concept type, analyzing each of the plurality of the terms to identify a linking term having a type that is the relationship type, where the linking term links the pair of terms in the knowledge model database, and including the linking term in the query. 
     
     
         15 . A non-transitory computer-readable medium containing instructions that, when executed by a processor, cause the processor to perform the steps of:
 receiving, from a client computer, a natural language query using a computer network;   analyzing the natural language query to identify a plurality of terms;   
       identifying a first entity in a knowledge model database that is related to at least one term in a pair of terms selected from the plurality of terms, the knowledge model database defining a plurality of entities and interrelationships between one or more of the plurality of entities for a knowledge domain;
 constructing a triple statement including the pair of terms and the first entity in the knowledge model database; 
 executing a query against a knowledge base using the triple statement to generate a set of results, the knowledge base identifying a plurality of items, each of the plurality of items being associated with at least one annotation identifying at one of the entities in the knowledge model database; and 
 transmitting, to the client computer, the set of results. 
 
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , including instructions that, when executed by a processor, cause the processor to perform the steps of:
 analyzing the natural language query using named entity recognition.   
     
     
         17 . The non-transitory computer-readable medium of  claim 15 , including instructions that, when executed by a processor, cause the processor to perform the steps of:
 determining a distance between each term in the pair of terms using the knowledge model database.   
     
     
         18 . The non-transitory computer-readable medium of  claim 17 , including instructions that, when executed by a processor, cause the processor to perform the steps of, when the distance between each term in the pair of terms is two or greater, discarding the pair of terms. 
     
     
         19 . The non-transitory computer-readable medium of  claim 15 , including instructions that, when executed by a processor, cause the processor to perform the steps of:
 determining a type of each term in the pair of terms, where the type is one of an instance type, a concept type, and a relationship type.   
     
     
         20 . The non-transitory computer-readable medium of  claim 19 , including instructions that, when executed by a processor, cause the processor to perform the steps of, when the type of each term in the pair of terms is the instance type or the concept type, analyzing each of the plurality of the terms to identify a linking term having a type that is the relationship type, where the linking term links the pair of terms in the knowledge model database, and including the linking term in the query.