title: wordnet alternatives to find semantic relationships between words python
body: <p>i have a project to get semantic relationships between two words , i want to get word to word relationships like hypernyms,hyponyms, Synonyms, holonyms, ...
  i try wordnet nltk but most of relationships is none,
  here is sample code:</p>
  <pre><code>from nltk.corpus import wordnet as wn
  from wordhoard import synonyms
  
  Word1 = 'red'
  Word2 = 'color'
  LSTWord1 =[]
  for syn in wn.synsets(Word1):
      for lemma in syn.part_meronyms():
          LSTWord1.append(lemma)
  
              
  for s in LSTWord1:
      if Word2 in s.name() :
          print(Word1 +' is meronyms  of ' +  Word2) 
          break
  LSTWord2 =[]
  for syn in wn.synsets(Word2):
      for lemma in syn.part_meronyms ():
          LSTWord2.append(lemma)
  
  for s in LSTWord2:
      if Word1 in s.name() :
          print( Word2   +' is meronyms  of ' + Word1)
          break
  
  
  </code></pre>
  <p>here an example of words:</p>
  <pre><code>scheduled ,geometry
  games,river
  campaign,sea
  adventure,place
  session,road
  long,town
  campaign,road
  session,railway
  difficulty of session,place of interest
  campaign,town
  leader,historic place
  have,town
  player,town
  skills,church
  campaign,cultural interest
  character name,town
  player,monument
  player,province
  games,beach
  expertise level,gas station
  character,municipality
  world,electrict line
  social interaction,municipality
  world,electric line
  percentage,municipality
  character,hospital
  inhabitants,mine
  active character,municipality
  campaign,altitude
  died,municipality
  many time,mountain
  adventurer,altitude
  campaign,peak
  gain,place of interest
  new capabilities,cultural interest
  player,cultural interest
  achievement,national park
  campaign,good
  first action,railway station
  player,province
  
  </code></pre>
  <p>may wordnet is limit or may there is no relation between words, my question is there any alternatives to wordnet to handle semantic relationships between words, or is there any better way to get semantic relation between words?
  Thanks</p>