Extended Data Fig. 9 |. Evaluating how well different word embeddings capture conceptual category structure.

Each matrix shows Pearson’s correlations between all pairs of word vectors for all items used in our study, grouped by category (indicated on the y-axis), for a different embedding. Color corresponds to correlation strength, with dark blue corresponding to −1 and red corresponding to 1. Qualitatively, all three embeddings capture categorical structure, as is evidenced by the block-diagonal structure of the correlation matrix. Nonetheless, ELMo appears to generate highly similar vectors for words sharing a category (the diagonal blocks are colored in strong red), indicating a poorer ability to distinguish among within-category items, compared to the other two embeddings. In contrast, BERT appears to separate items from across different categories more poorly than the other two embeddings (the color differences between the diagonal blocks and the rest of the matrix are somewhat weak).