17747463. AUTOMATED FACT CHECKING USING ITERATIVE KNOWLEDGE BASE QUERYING simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

AUTOMATED FACT CHECKING USING ITERATIVE KNOWLEDGE BASE QUERYING

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

G P Shrivatsa Bhargav of Bengaluru (IN)

Saswati Dana of Bangalore (IN)

Dinesh Khandelwal of Indore (IN)

Dinesh Garg of Ajmer Road (IN)

AUTOMATED FACT CHECKING USING ITERATIVE KNOWLEDGE BASE QUERYING - A simplified explanation of the abstract

This abstract first appeared for US patent application 17747463 titled 'AUTOMATED FACT CHECKING USING ITERATIVE KNOWLEDGE BASE QUERYING

Simplified Explanation

The patent application describes a method for decomposing a natural language assertion into a question and answer pair. This involves translating the question into a structured knowledge graph query and performing an iterative process of querying the knowledge graph and evaluating the responses.

• The method decomposes a natural language assertion into a question and answer pair.
• It translates the question into a structured knowledge graph query.
• The method performs an iterative process of querying the knowledge graph and evaluating the responses.
• In each iteration, the method retrieves a predicted answer and checks its similarity with the initial answer.
• If the similarity does not meet a threshold criterion, the query is altered and used for the next iteration.
• The method also generates an assertion correctness score based on the confidence scores obtained during the iterative process.

Potential Applications

• Natural language processing systems
• Question-answering systems
• Knowledge graph-based search engines

Problems Solved

• Difficulty in decomposing natural language assertions into question and answer pairs
• Inefficient querying of knowledge graphs for accurate answers
• Lack of confidence scoring for factual assertions

Benefits

• Improved accuracy in decomposing natural language assertions
• Efficient querying of knowledge graphs for accurate answers
• Confidence scoring to assess the correctness of assertions

Original Abstract Submitted

An embodiment includes decomposing a natural language assertion into a natural language question and answer pair that includes an initial question and an initial answer. The embodiment translates the initial question into a structured knowledge graph query and then performs an iterative process comprising iterative querying of a knowledge graph and evaluating of corresponding query responses resulting in respective confidence scores. A first iteration of the iterative process comprises querying of the knowledge graph to retrieve a first predicted answer, then determining whether a degree of similarity between the initial answer and the first predicted answer meets a threshold criterion. If not, the first predicted query is altered and used for querying the knowledge graph in a subsequent iteration of the iterative process. The embodiment also generates an assertion correctness score indicative of a degree of confidence that the assertion is factual using the respective confidence scores.