def apply(self, sentence, mention, features):
# head_index = HeadFeature.get_head(sentence, mention)
# for dep_type, gov, dep in sentence.dep:
# if head_index == gov:
# token = 'root'
# if dep >= 0:
# token = get_lemma(sentence.tokens[dep], sentence.pos[dep])
# features.append('ROLE_gov:%s' % dep_type)
# features.append('PARENT_%s' % token)
# if head_index == dep:
# token = 'root'
# if gov >= 0:
# token = get_lemma(sentence.tokens[dep], sentence.pos[gov])
# features.append('ROLE_dep:%s' % dep_type)
# features.append('PARENT_%s' % token)
start = mention.start
end = mention.end
for dep_type, gov, dep in sentence.dep:
if start <= gov < end:
if 0 <= dep < sentence.size():
token = get_lemma(sentence.tokens[dep], sentence.pos[dep])
pos = sentence.pos[dep]
if self.accept_pos(pos) and self.accept_dep(dep_type):
key = "gov:" + dep_type + ":" + token + "=" + pos[0]
features.append(("DEP_" + key))
if start <= dep < end:
if 0 <= gov < sentence.size():
token = get_lemma(sentence.tokens[gov], sentence.pos[gov])
pos = sentence.pos[gov]
if self.accept_pos(pos) and self.accept_dep(dep_type):
key = "dep:" + dep_type + ":" + token + "=" + pos[0]
features.append(("DEP_" + key))
def apply(self, sentence, mention, features):
# head_index = HeadFeature.get_head(sentence, mention)
# for dep_type, gov, dep in sentence.dep:
# if head_index == gov:
# token = 'root'
# if dep >= 0:
# token = get_lemma(sentence.tokens[dep], sentence.pos[dep])
# features.append('ROLE_gov:%s' % dep_type)
# features.append('PARENT_%s' % token)
# if head_index == dep:
# token = 'root'
# if gov >= 0:
# token = get_lemma(sentence.tokens[dep], sentence.pos[gov])
# features.append('ROLE_dep:%s' % dep_type)
# features.append('PARENT_%s' % token)
start = mention.start
end = mention.end
for dep_type, gov, dep in sentence.dep:
if start <= gov < end:
if 0 <= dep <sentence.size():
token = get_lemma(sentence.tokens[dep], sentence.pos[dep])
pos = sentence.pos[dep]
if self.accept_pos(pos) and self.accept_dep(dep_type):
key = "gov:" + dep_type + ":" + token + "=" + pos[0]
features.append(("DEP_" + key))
if start <= dep < end:
if 0 <= gov < sentence.size():
token = get_lemma(sentence.tokens[gov], sentence.pos[gov])
pos = sentence.pos[gov]
if self.accept_pos(pos) and self.accept_dep(dep_type):
key = "dep:" + dep_type + ":" + token + "=" + pos[0]
features.append(("DEP_" + key))
def apply(self, sentence, mention, features):
for i in xrange(len(sentence.tokens)):
word = get_lemma(sentence.tokens[i], sentence.pos[i])
if word in self.mapping:
cluster = self.mapping[word]
for l in self.len:
if len(cluster) >= l:
features.append('BROWN_%d_%s' % (l, cluster[0:l]))
features.append('BROWN_ALL_%s' % cluster)
def apply(self, sentence, mention, features):
for i in xrange(mention.start,mention.end):
word = get_lemma(sentence.tokens[i], sentence.pos[i])
if word in self.mapping:
cluster = self.mapping[word]
for l in self.len:
if len(cluster) >= l:
features.append('BROWN_%d_%s' % (l, cluster[0:l]))
features.append('BROWN_ALL_%s' % cluster)