Contract Clause-to-Provision Transformation Task
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A Contract Clause-to-Provision Transformation Task is a contract NLP task that converts contract clause ((in contract document) into discrete, identifiable contractual provision).
- Context:
- It can (typically) involve Legal Stipulation Recognition or Legal Condition Recognition.
- It can range from handling One-to-One Correspondence to Many-to-One Relationships in legal text structuring.
- It can be supported by a Contract Clause-to-Provision Transformation System (that implements a contract Clause-to-Provision Transformation algorithm).
- ...
- Example(s):
- one to support in Contract Analysis.
- one to prepare summaries of lengthy legal agreements for quick review.
- ...
- Counter-Example(s):
- Sentence Splitting Tasks, which simply break text into sentences without analyzing or extracting legal provisions.
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- See: Legal Text Analysis, Provision Type Recognition Task, Contract Review AI Platform.
References
2024
- Claude 3
- The relationship between provisions and sentences in legal writing can be complex. There are three main types of relationships to consider:
- One-to-one: A single sentence contains a single provision.
Example: "The parties agree to maintain confidentiality of all proprietary information shared during the course of this agreement."
- One-to-many: A single sentence contains multiple provisions, often listing several conditions, requirements, or exceptions.
Example: "The supplier shall deliver the goods within 30 days of receiving the order, provide a detailed invoice, and ensure that the goods meet all quality standards specified in Exhibit A."
- Many-to-one: Multiple sentences work together to convey a single provision, often when a complex provision requires detailed explanation.
Example: "The tenant shall be responsible for all utility payments during the lease term. This includes electricity, water, gas, and sewage. The tenant must provide proof of payment to the landlord upon request."