Back to indexSearch workflowMar 30, 20265 min

From Search Result to Full Article

How to move from keyword or semantic search into the full constitutional text and confirm whether a promising result really supports your research claim.

Open atlas Official ConstitutionalMap AI tutorial playlist Country Selection and Semantic Map View

Two entry points

Keyword search is better when you already know the expression or institution you want to test. Semantic search is better when you want conceptually related passages even if the wording changes across constitutions.

In practice, the two modes work best together: exact search to anchor yourself, semantic search to widen the field.

Validate before you conclude

The snippet is only a triage tool. The real validation happens when you open the full article and inspect nearby points in the same cluster.

Run a short keyword or semantic query.
Open a result that looks strong and read the full article.
Check the global cluster and inspect nearby segments.
Compare two or three full texts before keeping the claim.

How to read the visualization

What You Are Seeing

Each point in the 3D view represents a constitutional article or other meaningful legal unit. Nearby points are not nearby because they come from the same country, but because the language of those passages is semantically similar. Use country selection to compare how different constitutions occupy the same semantic terrain.

The map and the country list are selection tools. They decide which constitutions are loaded into the scene. Selecting more countries does not change the geometry of the embedding itself; it changes which parts of that global semantic space you can inspect.

Semantic Space

The embedding turns legal text into vectors, and the clustering step groups vectors that tend to discuss related constitutional themes. In country mode, color shows political origin. In cluster mode, color shows thematic neighborhood.

Large, dense clouds usually indicate recurring constitutional ideas such as rights, institutions, emergency powers, elections, or amendment rules. Isolated points often mark unusual provisions, rare wording, or country-specific constitutional design choices.

The platform offers two types of search: keyword search finds literal term occurrences, while semantic search retrieves conceptually nearby passages even without matching terms. Search results highlight regions of the semantic space in the 3D canvas, linking what you read to where it sits.

How to Read the Metrics

In the country statistics, Coverage measures how much of the global cluster landscape a constitution reaches. Entropy measures how evenly its segments are distributed across that landscape: high entropy suggests a broader semantic spread, while low entropy suggests concentration in fewer themes.

In the article detail panel, Global Cluster is the identifier of the thematic group assigned to that segment in the worldwide clustering. When the value is -1, it means the segment was left outside the defined thematic groupings in that global step. Probability indicates how confidently the clustering model placed that segment in that group: higher values mean a cleaner fit, while lower values usually mark more ambiguous or boundary cases.