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Your word
measured
“Pleistocene vegetation”
Definitions come from WordNet, a hand-curated dictionary.
all the plant life in a particular region or period
flora is Spanish for vegetation, 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.
“Pleistocene vegetation”
Definitions come from WordNet, a hand-curated dictionary.
This panel splits flora itself, not vegetation — 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.
fauna is the dictionary opposite of vegetation, yet this model puts it closer than every one of the 2 synonyms it can score. Opposites share the sentences a word lives in, so cosine alone cannot tell them apart - which is why the dictionary seeds this list rather than the geometry.
Shade shows how close the model puts each word to vegetation.
fauna is the dictionary opposite of vegetation, yet this model puts it closer than 1 of the 2 synonyms it can score. Opposites share the sentences a word lives in, so cosine alone cannot tell them apart - which is why the dictionary seeds this list rather than the geometry.
Shade shows how close the model puts each word to vegetation, 1 of 8 also appear in the dictionary.
This model splits vegetation 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.
fauna is the dictionary opposite of vegetation, yet this model puts it closer than 1 of the 2 synonyms it can score. Opposites share the sentences a word lives in, so cosine alone cannot tell them apart - which is why the dictionary seeds this list rather than the geometry.
Shade shows how close the model puts each word to vegetation.
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 vegetation 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 vegetation. 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 vegetation. That gap is the model’s own learned association.
This model splits vegetation 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 vegetation. That gap is the model’s own learned association.
These are statistical associations in the training data, not the model thinking.