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metadata
license: mit
tags:
  - infinite-dataset-hub
  - synthetic

GovQualityAssessment

tags: Government Contracts, QA, Classification

Note: This is an AI-generated dataset so its content may be inaccurate or false

Dataset Description:

The 'GovQualityAssessment' dataset is designed to facilitate the machine learning (ML) process of quality assessment (QA) for government contracts. Each record in the dataset corresponds to a specific contract proposal and includes detailed textual information as well as a label indicating the overall quality of the proposal. The labels are assigned based on predefined criteria such as completeness, clarity, adherence to guidelines, and compliance. The dataset aims to assist ML practitioners in developing models that can automatically classify contract proposals as either 'High Quality' or 'Low Quality' to improve the efficiency and reliability of the contract awarding process.

CSV Content Preview:

"Contract Proposal ID","Contract Proposal Description","Label"
"001","Comprehensive proposal with detailed budget breakdown and clear deliverables for constructing a government facility. Fully compliant with all contract guidelines.","High Quality"
"002","Proposal with vague descriptions and lacking specific project timelines. Does not meet the required detail level.","Low Quality"
"003","Detailed proposal covering all necessary aspects including regulatory compliance and financial accountability. Exceptional clarity in objectives and methodologies.","High Quality"
"004","Incomplete proposal missing critical sections such as risk management and resource allocation. Does not follow the standard contract format.","Low Quality"
"005","Proposal outlines innovative approaches to public infrastructure development with thorough justification for budget estimates. Strong alignment with governmental objectives.","High Quality"

Source of the data:

The dataset was generated using the Infinite Dataset Hub and microsoft/Phi-3-mini-4k-instruct using the query 'Government contract QA':