1
Your word
measured
“cosmetic fenders on cars”
Definitions come from WordNet, a hand-curated dictionary.
serving an esthetic rather than a useful purpose
decorativo is Spanish for decorative, and every measurement below was made on that English word. Definitions come from English WordNet; Open Multilingual WordNet supplies the Spanish headword, not a Spanish definition.
Panels 3, 4 and 5 are computed per model. Switch to see them disagree.
“cosmetic fenders on cars”
Definitions come from WordNet, a hand-curated dictionary.
This panel splits decorativo itself, not decorative — a tokenizer does not care what language it is fed. It is the only panel here that does.
This is the tokenizer splitting text, not the model understanding it.
Shade shows how close the model puts each word to decorative, 1 of 8 also appear in the dictionary.
Shade shows how close the model puts each word to decorative, 1 of 8 also appear in the dictionary.
This model splits decorative into 2 pieces, so it has no vector of its own here: this is the average of its fragments, and the results below are correspondingly rough.
Shade shows how close the model puts each word to decorative.
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.
This model splits decorative into 2 pieces, so it has no vector of its own here: this is the average of its fragments, and the results below are correspondingly rough.
Scores are projections onto axes we defined from anchor words, not labels the model assigns.
These sit just outside the closest neighbours in panel 3, and no dictionary lists any of them as related to decorative. 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 decorative. That gap is the model’s own learned association.
This model splits decorative into 2 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 decorative. That gap is the model’s own learned association.
These are statistical associations in the training data, not the model thinking.