Amendment and legislative text similarity assessment tool

Bill drafting and amendments

Italy - Senate

Use case ID: 036

Author: Senate of Italy

Date: 12 June 2024 

Objective:

Assess the degree of similarity among legislative texts and group them into clusters based on their similarities.

Actors:

  • Senate users (e.g. documentalists and legislative analysts)

Prerequisites:

  • Basic knowledge of computer tools
  • Domain-specific knowledge of legislative texts and related documents

Scenario:

  1. A Senate documentalist selects a series of texts of the same type, such as legislative articles or amendments.
  2. The user employs an application that analyses the selected texts and groups them into clusters based on their similarity.
  3. The documentalist reviews the resulting clusters to ensure they meet the chosen similarity metric and are logically grouped.

Alternate flows:

  • If the initial clustering results are unsatisfactory, the documentalist can adjust the similarity parameters or criteria and reprocess the texts.

Expected results:

  • Similar legislative texts are grouped accurately according to the defined similarity metrics.
  • Clustering results are consistent, with minimal changes in the number and size of clusters as the set of documents evolves.

Potential challenges:

  • Ensuring users understand the concept and implementation of the similarity metric
  • Adapting similarity algorithms to the specific characteristics and requirements of legislative texts
  • Handling large volumes of text efficiently without compromising accuracy

Data requirements:

  • A comprehensive set of legislative texts for comparison (e.g. articles and amendments)
  • Historical clustering results to fine-tune and validate the similarity algorithms

Integrations with other systems:

  • Potential integration with legislative databases and document management systems for seamless retrieval and processing of texts

Success metrics:

  • Stability of clusters in terms of number and size across subsequent iterations
  • Similarity metrics that are transparent and understandable to end users
  • High user satisfaction with the accuracy and usefulness of the clustered groupings

 

The Use cases for AI in parliaments collection is published by the IPU’s Centre for Innovation in Parliament as part of the Parliamentary Data Science Hub’s project to create guidelines for AI governance in parliaments.

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