Table 1.
Prime and target word characteristics of 264 word pair triplets: Length, word frequency (Zipf values [30]), and the semantic relatedness values (cosine similarity scores) for the strongly related, weakly related, and unrelated conditions tested in Survey 1 and Survey 2.
Table 2.
Examples of strongly related, weakly related and unrelated prime words together with target words in Polish selected for Survey 1 and Survey 2 (translations in English are provided in parentheses).
Fig 1.
Scatterplot of the rating data from Survey 1 and 2.
Table 3.
Mean ratings and standard deviations (in parentheses) for the three conditions in Survey 1 and Survey 2.
Table 4.
Prime and target word characteristics of 216 word pair triplets: Length, word frequency (Zipf values), and the semantic relatedness values (cosine similarity scores) for the strongly related, weakly related, and unrelated conditions tested in Experiment 2.
Fig 2.
Mean reaction times and standard errors for the three priming conditions in Experiment 2.
Table 5.
Mean reaction times in milliseconds with standard deviations (in parentheses) and error rates for the priming conditions in each set and both sets combined in Experiment 2.
Table 6.
List of hyperparameters and possible values, and hyperparameter values of the semantic space identified as optimal.
For more information about the meaning of each hyperparameter see gensim documentation (https://radimrehurek.com/gensim/models/word2vec.html#gensim.models.word2vec.Word2Vec).
Table 7.
The predictiveness of the linear models using the optimized semantic model hyperparameters.
These performance numbers can be considered to represent the estimated performance of the models on the independent datasets.
Fig 3.
Scatterplot showing the relationship between the semantic space similarity estimates (nkjp+wiki-lemmas-restricted-300-cbow-ns.txt.gz, [11]) and the human similarity ratings.