Text Inputs
Enter 3–6 short texts, or start with one of the example sets below. The map will place them based on lexical similarity (a simple stand-in for embeddings).
Selecting an example will automatically fill Text 1–6 so you can see how similar items cluster on the map. You can edit any of the texts before building the map.
Embeddings-Style Map
No map yet. Add 3–6 texts or select an example set, then click Build Map.
2D Similarity Layout
Closer points ≈ more similar meaning (by lexical overlap).
Map preview will appear here.
Position is computed from pairwise similarity only — there is no “correct” orientation, just relative distance.
Similarity Matrix
Values are cosine similarity scores on simple bag-of-words vectors (0 = unrelated, 1 = identical).
Interpretation Notes
Once a map is generated, this section summarizes which texts are most similar, which are isolated, and how clusters emerge.