cardiovascular

adjective 1 sense

of or pertaining to or involving the heart and blood vessels

Qwen3 8B
DeepSeek V3
Mistral 7B

Panels 3, 4 and 5 are computed per model. Switch to see them disagree.

1 Your word measured

“cardiovascular conditioning”

adjective 1 sense 0 synonyms

Definitions come from WordNet, a hand-curated dictionary.

2 To an AI, it's pieces measured
DeepSeek V3 cardiovascular 1 token
Mistral 7B card iov ascular 3 tokens
Qwen3 8B cardiovascular 1 token

This is the tokenizer splitting text, not the model understanding it.

3 Synonyms, antonyms, and the AI measured
Qwen3 8B
DeepSeek V3
Mistral 7B

Shade shows how close the model puts each word to cardiovascular.

Shade shows how close the model puts each word to cardiovascular.

This model splits cardiovascular into 3 pieces, so it has no vector of its own here: this is the average of its fragments, and the results below are correspondingly rough.

Dictionary synonyms measured

WordNet lists none for this word.

Shade shows how close the model puts each word to cardiovascular.

Model neighbours are distributional, not dictionary synonyms. Two words can be close because they appear in similar sentences, which is why an antonym can outscore a synonym here.

4 Its personality measured
Qwen3 8B
DeepSeek V3
Mistral 7B
rare common
concrete abstract
casual formal
everyday technical
negative positive
mild intense
powerless powerful
small big
rare common
concrete abstract
casual formal
everyday technical
negative positive
mild intense
powerless powerful
small big

This model splits cardiovascular into 3 pieces, so it has no vector of its own here: this is the average of its fragments, and the results below are correspondingly rough.

rare common
concrete abstract
casual formal
everyday technical
negative positive
mild intense
powerless powerful
small big

Scores are projections onto axes we defined from anchor words, not labels the model assigns.

5 Surprising neighbours measured
Qwen3 8B
DeepSeek V3
Mistral 7B

These sit just outside the closest neighbours in panel 3, and no dictionary lists any of them as related to cardiovascular. That gap is the model’s own learned association.

These sit just outside the closest neighbours in panel 3, and no dictionary lists any of them as related to cardiovascular. That gap is the model’s own learned association.

This model splits cardiovascular into 3 pieces, so it has no vector of its own here: this is the average of its fragments, and the results below are correspondingly rough.

These sit just outside the closest neighbours in panel 3, and no dictionary lists any of them as related to cardiovascular. That gap is the model’s own learned association.

These are statistical associations in the training data, not the model thinking.