1
Your word
measured
“You have to be a good observer to see all the details”
Definitions come from WordNet, a hand-curated dictionary.
perceive by sight or have the power to perceive by sight
Panels 3, 4 and 5 are computed per model. Switch to see them disagree.
“You have to be a good observer to see all the details”
Definitions come from WordNet, a hand-curated dictionary.
This is the tokenizer splitting text, not the model understanding it.
Shade shows how close the model puts each word to seen, 1 of 8 also appear in the dictionary. 39 of 55 dictionary synonyms are in this build; the rest have no vector to compare yet.
Shade shows how close the model puts each word to seen, 1 of 8 also appear in the dictionary. 39 of 55 dictionary synonyms are in this build; the rest have no vector to compare yet.
Shade shows how close the model puts each word to seen, 1 of 8 also appear in the dictionary. 39 of 55 dictionary synonyms are in this build; the rest have no vector to compare yet.
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.
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 seen. 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 seen. 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 seen. That gap is the model’s own learned association.
These are statistical associations in the training data, not the model thinking.