Python nltk.util() Examples
The following are 3
code examples of nltk.util().
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Example #1
| Source File: wordnet.py From razzy-spinner with GNU General Public License v3.0 | 6 votes |
|
def closure(self, rel, depth=-1):
"""Return the transitive closure of source under the rel
relationship, breadth-first
>>> from nltk.corpus import wordnet as wn
>>> dog = wn.synset('dog.n.01')
>>> hyp = lambda s:s.hypernyms()
>>> list(dog.closure(hyp))
[Synset('canine.n.02'), Synset('domestic_animal.n.01'),
Synset('carnivore.n.01'), Synset('animal.n.01'),
Synset('placental.n.01'), Synset('organism.n.01'),
Synset('mammal.n.01'), Synset('living_thing.n.01'),
Synset('vertebrate.n.01'), Synset('whole.n.02'),
Synset('chordate.n.01'), Synset('object.n.01'),
Synset('physical_entity.n.01'), Synset('entity.n.01')]
"""
from nltk.util import breadth_first
synset_offsets = []
for synset in breadth_first(self, rel, depth):
if synset._offset != self._offset:
if synset._offset not in synset_offsets:
synset_offsets.append(synset._offset)
yield synset
Example #2
| Source File: wordnet.py From luscan-devel with GNU General Public License v2.0 | 6 votes |
|
def closure(self, rel, depth=-1):
"""Return the transitive closure of source under the rel
relationship, breadth-first
>>> from nltk.corpus import wordnet as wn
>>> dog = wn.synset('dog.n.01')
>>> hyp = lambda s:s.hypernyms()
>>> list(dog.closure(hyp))
[Synset('domestic_animal.n.01'), Synset('canine.n.02'), Synset('animal.n.01'), Synset('carnivore.n.01'), Synset('organism.n.01'), Synset('placental.n.01'), Synset('living_thing.n.01'), Synset('mammal.n.01'), Synset('whole.n.02'), Synset('vertebrate.n.01'), Synset('object.n.01'), Synset('chordate.n.01'), Synset('physical_entity.n.01'), Synset('entity.n.01')]
"""
from nltk.util import breadth_first
synset_offsets = []
for synset in breadth_first(self, rel, depth):
if synset.offset != self.offset:
if synset.offset not in synset_offsets:
synset_offsets.append(synset.offset)
yield synset
Example #3
| Source File: wsj10.py From struct-learning-with-flow with MIT License | 4 votes |
|
def _generate_trees(self):
# trees = util.load_obj(self.filename + '_gold_len10')
trees = None
if trees is None:
print("Parsing treebank...")
f = lambda t: len(t.leaves()) <= self.n
m = lambda t: self._prepare(t)
# f = lambda t: t
# m = lambda t: t
trees = [t for t in filter(f, map(m, self.parsed()))]
# util.save_obj(trees, self.filename + '_gold_len10')
# w/o filtering
# trees = [t for t in self.parsed()]
# add hmm induced tags
if self.extra_tags is not None:
# new_trees = util.load_obj(self.filename + '_35_len10')
new_trees = None
if new_trees is None:
new_trees = []
# cnt = 0
for t, tags in zip(self.parsed(), self.extra_tags):
# if cnt % 100 == 0:
# print cnt
# cnt += 1
for st, tag in zip(t.subtrees(lambda x: x.height() == 2), tags):
st.insert(0, tag)
t = self._prepare(t)
if len(t.leaves()) / 2 <= self.n:
new_trees += [t]
# util.save_obj(new_trees, self.filename + '_35_len10')
self.gold_tag_sents = [[(sub.label(), sub.leaves()[0]) \
for sub in t.subtrees(lambda x: x.height() == 2)] \
for t in trees]
if self.extra_tags is not None:
self.induce_tag_sents = [[(sub.leaves()[0], sub.leaves()[1]) \
for sub in t.subtrees(lambda x: x.height() == 2)] \
for t in new_trees]
else:
self.induce_tag_sents = None
return trees
