Summary of Answering Questions in Stages: Prompt Chaining For Contract Qa, by Adam Roegiest et al.
Answering Questions in Stages: Prompt Chaining for Contract QA
by Adam Roegiest, Radha Chitta
First submitted to arxiv on: 9 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a novel approach to analyzing legal contracts at scale. Existing methods using large language models with simple prompts can generate structured answers to basic questions but struggle with complex clauses containing irrelevant information. The proposed two-stage prompt chaining technique improves performance on nuanced legal text by generating more effective prompts for multiple-choice and multiple-select questions. The authors analyze scenarios where this method excels and areas requiring further refinement, particularly when linguistic variations exceed possible answer specifications. Finally, the paper discusses future research directions to enhance stage one results by making them question-specific. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research helps computers better understand legal documents by breaking down complex questions into smaller, more manageable parts. Right now, computers can give simple answers to basic questions, but they struggle with longer contracts containing irrelevant information. The new approach, called two-stage prompt chaining, makes it easier for computers to provide accurate answers even in complicated cases. The authors explore when this method works well and where it needs improvement. They also discuss ways to make the technique even better by making it more specific to each question. |
Keywords
* Artificial intelligence * Prompt
