Prompt-based missing entity recovery for solving arithmetic word problems

This paper addresses the challenge of missing entity recovery in arithmetic word problems using prompt-based techniques. The approach leverages natural language prompts to guide the system in identifying and recovering missing mathematical entities that are crucial for problem solving.

Key Contributions

1. Prompt-based Framework: Novel use of prompts for entity recovery in mathematical problem solving
2. Missing Entity Detection: Systematic approach to identify missing entities in word problems
3. Recovery Strategies: Effective methods for reconstructing missing information
4. Performance Improvement: Enhanced accuracy in arithmetic word problem solving

Methodology

The proposed approach includes:

• Entity Analysis: Comprehensive analysis of entities in word problems
• Missing Entity Identification: Detection of implicit or missing entities
• Prompt Design: Crafting effective prompts for entity recovery
• Recovery Process: Systematic recovery of missing entities
• Integration: Seamless integration with existing problem solving systems

This work contributes to the advancement of automated mathematical problem solving by addressing a key challenge in natural language understanding for educational applications.