Frequency of (non)-colexification against WordNet relationship types
df_freq_pos <- df_freq %>% filter(type=='colex_pos')
tapply(df_freq_pos$freq, df_freq_pos$wn.relation, summary)
## $antonymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 0.00 8.35 4.00 102.00
##
## $hypernymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 0.000 1.000 9.438 6.000 235.000
##
## $meronymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 2.00 23.45 19.50 300.00
##
## $no.rel
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0000 0.0000 0.1412 0.0000 263.0000
df_freq_neg <- df_freq %>% filter(type=='colex_neg')
tapply(df_freq_neg$freq, df_freq_neg$wn.relation, summary)
## $antonymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 36.0 284.8 452.0 580.8 700.2 1830.0
##
## $hypernymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 10.0 158.2 245.0 294.8 332.5 1924.0
##
## $meronymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 30.0 288.5 584.0 618.5 774.5 1971.0
##
## $no.rel
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.0 129.0 223.0 245.2 303.0 2076.0
tapply(df_prop$colex.prop, df_prop$wn.relation, summary)
## $antonymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000000 0.000000 0.000000 0.017144 0.004884 0.227692
##
## $hypernymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000000 0.000000 0.003098 0.040312 0.036972 0.545454
##
## $meronymy
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000000 0.000000 0.003802 0.037331 0.032796 0.372294
##
## $no.rel
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000000 0.0000000 0.0000000 0.0004481 0.0000000 0.8694030
This pretty much mirrors the plot above