Advancing NLP with Cognitive Language Processing Signals
Table 2: The top part shows the size of the datasets used for the type-aggregation experiments, including the percentage of unknown tokens, i.e. tokens not in the lexicon of aggregated type features. The bottom part shows F1-scores of type aggregation on external benchmark corpora. Significance is indicated with the asterisks: * = p<0.01, ** = p<0.0008 (Bonferroni method).
['[EMPTY]', '[BOLD] NER', '[BOLD] RelClass', '[BOLD] Sentiment (2)', '[BOLD] Sentiment (3)']
We can observe a consistent improvement using type-aggregated gaze features. However, the effect of type-aggregated EEG features is mixed.