class WordNetLookup(object):
def __init__(self, path='corpora/wordnet'):
self.path = path
self.WN = None
def wn(self):
if not self.WN:
self.WN = WordNetCorpusReader(nltk.data.find(self.path))
def is_superclass_of(self, first, second):
"Is the second noun the superclass of the first one?"
self.wn()
# We cannot guarantee it is a noun. By the time we deal with DRSs, this is just a condition, and could have easily
# come from an adjective (if the user does not provide features for nouns, as we do in our grammar)
try:
num_of_senses_first = self._num_of_senses(first)
num_of_senses_second = self._num_of_senses(second)
except:
return False
# At first I wanted to take the first senses of both words, but the first sense is not always the basic meaning of the word, e.g.:
# S('hammer.n.1').definition: the part of a gunlock that strikes the percussion cap when the trigger is pulled'
# S('hammer.n.2').definition: 'a hand tool with a heavy rigid head and a handle; used to deliver an impulsive force by striking'
for n in range(num_of_senses_second):
synset_second = self._noun_synset(second, ind=n)
for i in range(num_of_senses_first):
#print synset_second, self._noun_synset(first, i).common_hypernyms(synset_second)
if synset_second in self._noun_synset(
first, i).common_hypernyms(synset_second):
#print "+++ first", first, "second", second, True
return True
return False
def is_adjective(self, word):
try:
self._num_of_senses(word, 'a')
return True
except:
return False
def _noun_synset(self, noun, ind):
self.wn()
return self.WN.synset("%s.n.%s" % (noun, ind))
def _num_of_senses(self, word, pos='n'):
self.wn()
return len(self.WN._lemma_pos_offset_map[word][pos])
def is_person(self, word):
return self.is_superclass_of(word, 'person')
def is_animal(self, word):
return self.is_superclass_of(word, 'animal')
class WordNetLookup(object):
def __init__(self, path='corpora/wordnet'):
self.path = path
self.WN = None
def wn(self):
if not self.WN:
self.WN = WordNetCorpusReader(nltk.data.find(self.path))
def is_superclass_of(self, first, second):
"Is the second noun the superclass of the first one?"
self.wn()
# We cannot guarantee it is a noun. By the time we deal with DRSs, this is just a condition, and could have easily
# come from an adjective (if the user does not provide features for nouns, as we do in our grammar)
try:
num_of_senses_first = self._num_of_senses(first)
num_of_senses_second = self._num_of_senses(second)
except: return False
# At first I wanted to take the first senses of both words, but the first sense is not always the basic meaning of the word, e.g.:
# S('hammer.n.1').definition: the part of a gunlock that strikes the percussion cap when the trigger is pulled'
# S('hammer.n.2').definition: 'a hand tool with a heavy rigid head and a handle; used to deliver an impulsive force by striking'
for n in range(num_of_senses_second):
synset_second = self._noun_synset(second, ind=n)
for i in range(num_of_senses_first):
#print synset_second, self._noun_synset(first, i).common_hypernyms(synset_second)
if synset_second in self._noun_synset(first, i).common_hypernyms(synset_second):
#print "+++ first", first, "second", second, True
return True
return False
def is_adjective(self, word):
try:
self._num_of_senses(word, 'a')
return True
except: return False
def _noun_synset(self, noun, ind):
self.wn()
return self.WN.synset("%s.n.%s" % (noun, ind))
def _num_of_senses (self, word, pos='n'):
self.wn()
return len(self.WN._lemma_pos_offset_map[word][pos])
def is_person(self, word):
return self.is_superclass_of(word, 'person')
def is_animal(self, word):
return self.is_superclass_of(word, 'animal')
class WordNetLookup(object):
def __init__(self, path='corpora/wordnet'):
self.path = path
self.WN = None
def wn(self):
if not self.WN:
self.WN = WordNetCorpusReader(nltk.data.find(self.path))
def is_superclass_of(self, first, second):
"Is the second noun the superclass of the first one?"
self.wn()
try:
num_of_senses_first = self._num_of_senses(first)
num_of_senses_second = self._num_of_senses(second)
except:
return False
for n in range(num_of_senses_second):
synset_second = self._noun_synset(second, ind=n)
for i in range(num_of_senses_first):
if synset_second in self._noun_synset(
first, i).common_hypernyms(synset_second):
return True
return False
def is_adjective(self, word):
try:
self._num_of_senses(word, 'a')
return True
except:
return False
def _noun_synset(self, noun, ind):
self.wn()
return self.WN.synset("%s.n.%s" % (noun, ind))
def _num_of_senses(self, word, pos='n'):
self.wn()
return len(self.WN._lemma_pos_offset_map[word][pos])
def is_person(self, word):
return self.is_superclass_of(word, 'person')
def is_animal(self, word):
return self.is_superclass_of(word, 'animal')
class WordNetLookup(object):
def __init__(self, path='corpora/wordnet'):
self.path = path
self.WN = None
def wn(self):
if not self.WN:
self.WN = WordNetCorpusReader(nltk.data.find(self.path))
def is_superclass_of(self, first, second):
"Is the second noun the superclass of the first one?"
self.wn()
try:
num_of_senses_first = self._num_of_senses(first)
num_of_senses_second = self._num_of_senses(second)
except: return False
for n in range(num_of_senses_second):
synset_second = self._noun_synset(second, ind=n)
for i in range(num_of_senses_first):
if synset_second in self._noun_synset(first, i).common_hypernyms(synset_second):
return True
return False
def is_adjective(self, word):
try:
self._num_of_senses(word, 'a')
return True
except: return False
def _noun_synset(self, noun, ind):
self.wn()
return self.WN.synset("%s.n.%s" % (noun, ind))
def _num_of_senses (self, word, pos='n'):
self.wn()
return len(self.WN._lemma_pos_offset_map[word][pos])
def is_person(self, word):
return self.is_superclass_of(word, 'person')
def is_animal(self, word):
return self.is_superclass_of(word, 'animal')
