Generating Clarification Questions for Disambiguating Contracts: ConRAP Framework

Core Concepts

In creating the ConRAP framework, the authors aim to assist non-legal stakeholders in identifying ambiguities in contractual clauses by generating clarification questions. The approach involves a retrieval-augmented prompting framework to enhance ambiguity detection and improve the quality of generated questions.

Abstract

The ConRAP framework introduces a novel legal NLP task focused on generating clarification questions for contracts to disambiguate contractual text. It addresses challenges such as data availability, contract complexity, and legal language. By combining attribute prompting and retrieval-augmented QA, ConRAP achieves an F2 score of 0.87 in ambiguity detection. Human evaluators found 70% of generated clarification questions useful. The framework enhances precision and recall in detecting ambiguities across various LLMs, with ChatGPT outperforming other baselines. Vicuna shows comparable results to ChatGPT in CQGen quality evaluation. Key points: Enterprises rely on commercial contracts for project-specific requirements. Comprehending contracts is challenging due to legalese and ambiguity. ConRAP introduces a novel legal NLP task for generating clarification questions. The framework addresses issues like data availability and contract complexity. ConRAP combines attribute prompting and retrieval-augmented QA for ambiguity detection. Evaluation shows improved precision, recall, and F2 score with ChatGPT. Human evaluators find 70% of generated clarification questions useful. Vicuna demonstrates comparable results to ChatGPT in CQGen quality evaluation.

Stats

Experiments show that ConRAP with ChatGPT can detect ambiguities with an F2 score of 0.87. 70% of the generated clarification questions are deemed useful by human evaluators.

Quotes

"Contracts often contain ambiguously worded clauses to ensure comprehensive coverage." "ConRAP significantly surpasses strong baselines, establishing its superior performance in ambiguity detection."

Key Insights Distilled From

Generating Clarification Questions for Disambiguating Contracts

by Anmol Singha... at arxiv.org 03-14-2024

https://arxiv.org/pdf/2403.08053.pdf

Deeper Inquiries

How can the ConRAP framework be adapted for use beyond contractual analysis?

The ConRAP framework, designed for generating clarification questions to pinpoint ambiguities in contractual text, can be adapted for broader applications beyond contract analysis. One way to adapt it is by incorporating domain-specific knowledge bases to enhance the understanding of specialized terminology and context in various industries. This adaptation would enable the framework to generate more accurate and relevant clarification questions tailored to specific domains such as healthcare, finance, or technology. Additionally, integrating real-time data sources could allow ConRAP to provide up-to-date information and insights for decision-making processes in dynamic environments. Furthermore, expanding the framework's capabilities to handle multilingual contracts or documents would make it versatile across different regions and languages.

What counterarguments exist against relying on AI-generated clarification questions?

While AI-generated clarification questions offer efficiency and scalability benefits in analyzing complex documents like contracts, there are several counterarguments that need consideration. One key concern is the potential lack of contextual understanding by AI models when generating these questions. Ambiguities or nuances present in legal language may not always be accurately captured by AI systems, leading to misleading or irrelevant queries being generated. Moreover, there is a risk of over-reliance on automated systems without human oversight, which could result in critical errors going unnoticed during requirements elicitation processes. Another counterargument revolves around privacy and confidentiality issues related to sensitive information contained within contracts; exposing such details through automated questioning poses a security risk if not handled carefully.

How might the concept of ambiguous clauses impact downstream implementation activities?

Ambiguous clauses within contracts can significantly impact downstream implementation activities by introducing uncertainty and confusion into project execution processes. When contractual terms are open to interpretation due to ambiguity, non-legal stakeholders involved in implementing project requirements may face challenges in clearly defining their tasks and responsibilities based on those clauses. This lack of clarity can lead to delays in decision-making, disputes among parties involved, increased costs due to rework or modifications needed post-implementation, and even legal implications if disagreements arise regarding obligations outlined in ambiguous clauses. Additionally, ambiguous clauses can hinder effective communication between different teams working on a project as each party may have varying interpretations of what is expected from them based on these unclear provisions.