Multi-hop Question Answering via Iterative Query Decomposition
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Solution Overview
Problem
Current question answering systems struggle to effectively address complex, multi-hop questions that require navigation through and integration of extensive information, as they are limited by fixed architectures that do not accommodate multi-hop reasoning well, especially when necessary facts are not retrieved in the first step.
Innovation Solution
The proposed solution employs a rule-based and clause-based reasoning system that decomposes complex questions into simpler queries, using formal reasoning and machine reading comprehension to iteratively retrieve information from various sources, integrating deduction and induction to infer new clauses and associate existing answers with questions, even when explicit information is lacking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed architecture question answering system is used, then the system structure is simple and easy to implement, but it cannot effectively handle complex multi-hop questions that require iterative reasoning
Solution Approach 1:
The patent segments complex multi-hop questions into multiple simpler sub-queries through iterative decomposition. The system breaks down a complex question into intermediate questions, answers each sub-query separately, and then integrates the results to form the final answer. This segmentation allows the system to handle complex reasoning tasks using a relatively simple fixed architecture by processing them in manageable steps.
2Adaptability or versatility
If iterative decomposition and recomposition is employed, then the system can handle complex queries with multi-hop reasoning, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and analyzing the complex question to identify its structural components and required reasoning steps before actual query execution. This preliminary decomposition allows the system to prepare the query breakdown in advance, reducing the computational overhead during the iterative answering process and optimizing overall processing time.
3Reliability
If formal reasoning and clause-based inference are used, then the system can infer new clauses and associate answers with questions lacking explicit information, but the reasoning complexity and computational load increase
Solution Approach 1:
The patent introduces an intermediary layer of formal logical clauses and inference rules that mediate between the raw question and the knowledge base. This intermediary reasoning layer enables the system to perform systematic logical inference, deriving new clauses and associating answers with questions that lack explicit information. The intermediary structure organizes the complexity of formal reasoning into manageable inference steps while maintaining reliability.
Data Source
AI summary
Systems, devices, and methods discussed herein provide improved autonomous agent applications that are configured to generate automated answers to a complex query (e.g., a query that includes more than one search parameter). A user query comprising a complex query may be received and decomposed into a number of simple queries. A simple query may be executed with a search engine to obtain a set of search results. An answer for the simple query may be obtained from the search results and then substituted for a term of the next simple query identified from the complex query. The next simple query may then be executed to obtain another set of search results. These steps may occur any suitable number of times. An answer for the complex query may be generated based at least in part on the answers one or more of the simple queries.