1
Your word
measured
“he will work here temporarily”
Definitions come from WordNet, a hand-curated dictionary.
for a limited time only; not permanently
一旦 is Japanese for temporarily, and every measurement below was made on that English word. Definitions come from English WordNet; Open Multilingual WordNet supplies the Japanese headword, not a Japanese definition.
Panels 3, 4 and 5 are computed per model. Switch to see them disagree.
“he will work here temporarily”
Definitions come from WordNet, a hand-curated dictionary.
3 of those are a raw byte rather than a character: Mistral 7B splits this word below the character, so no single token it sees is readable.
This panel splits 一旦 itself, not temporarily — 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.
WordNet lists none for this word.
Shade shows how close the model puts each word to temporarily.
WordNet lists none for this word.
Shade shows how close the model puts each word to temporarily.
WordNet lists none for this word.
Shade shows how close the model puts each word to temporarily.
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 temporarily. 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 temporarily. 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 temporarily. That gap is the model’s own learned association.
These are statistical associations in the training data, not the model thinking.