I understand that the following code iterates over all the synsets of syn1
with synsets of syn2
.
My question is, how to get the synset that gives the maximum score?
from nltk.corpus import wordnet
syn1 = wordnet.synsets('speed',pos='n')
syn2 = wordnet.synsets('performance',pos='n')
for word1 in syn1:
best = max(word1.path_similarity(word2) for word2 in syn2)
ps_list.append(best)
Maybe you need something like this:
import numpy as np
from nltk.corpus import wordnet
syn1 = wordnet.synsets('speed',pos='n')
syn2 = wordnet.synsets('performance',pos='n')
def getMaxPath(synset1,synset2):
sim=[]
a=[]
b=[]
for i in synset1:
for j in synset2:
sim.append(wordnet.path_similarity(i,j))
a.append(i.name()) # save the names from synsets1 into list
b.append(j.name()) # save the names from synsets2 into list
max_sim=max(sim)
idx=np.argmax(sim)
s1=a[idx] # get the name of synset1 for which path sim is max
s2=b[idx] # get the name of synset2 for which path sim is max
return max_sim, s1, s2
getMaxPath(syn1, syn2)
Output:
(0.2, 'speed.n.03', 'performance.n.03')
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