def get_dependency_features(feature_vector, dependency_list, generalization=None):
"""@param generalization: the generalization to apply, if any.
Appropriate values are: None, 'pos', 'opinion', 'liwc', 'neg_dist_opinion'
"""
for i in range(len(dependency_list)):
dependency_list[i]['governor_index'] = i
negations = dict([(dep['governor_index'],dep) for dep in dependency_list if dep['relation']=='neg'])
#Could stand to be reworked
for dep in dependency_list:
relation = dep['relation'].lower()
governor = dep['governor'].lower()
dependent = dep['dependent'].lower()
if generalization==None:
feature_vector['dependency:'+relation+'('+governor+', '+dependent+')']=True
elif generalization=='pos':
feature_vector['dep_'+generalization+'_generalized:'+relation+'('+mpqa.convert_pos(dep['governor_pos'])+', '+dependent+')']=True
elif generalization=='opinion':
gov_polarity = mpqa.lookup(governor, dep['governor_pos'])
if gov_polarity != None:
feature_vector['dep_'+generalization+'_generalized:'+relation+'('+gov_polarity['polarity']+', '+dependent+')']=True
dep_polarity = mpqa.lookup(dependent, dep['dependent_pos'])
if dep_polarity != None:
feature_vector['dep_'+generalization+'_generalized:'+relation+'('+governor+', '+dep_polarity['polarity']+')']=True
elif generalization=='neg_dist_opinion':
for element in ['dependent','governor']:
word = dep[element].lower()
polarity_dict = mpqa.lookup(word, dep[element+'_pos'])
if polarity_dict is not None:
polarity = polarity_dict['polarity']
element_index = dep[element+'_index']
if element_index in negations and relation!='neg':
if polarity=='negative':
polarity = 'positive'
elif polarity=='positive':
polarity = 'negative'
else: continue #TODO: This forces only flipped polarity deps to be included... is this desired?
if element == 'dependent':
feature_vector['dep_'+generalization+'_generalized:'+relation+'('+governor+', '+polarity+')']=True
else:
feature_vector['dep_'+generalization+'_generalized:'+relation+'('+polarity+', '+dependent+')']=True
elif generalization=='liwc':
gov_categories = word_category_counter.score_word(governor).keys()
gov_categories.append(governor)
dep_categories = word_category_counter.score_word(dependent).keys()
dep_categories.append(dependent)
for gov_category in gov_categories:
for dep_category in dep_categories:
if gov_category==governor and dep_category==dependent: continue #avoids the no generalization case
feature_vector['dep_'+generalization+'_generalized:'+relation+'('+gov_category+', '+dep_category+')']=True
def __init__(self, word, index, pos, rel=None, lemma=None, start=None, end=None):
'''
constructor
'''
self.next_tree = None
self.gov = None
self.deps = None
self.prev = None
self.nxt = None
self.dist = None
self.start = start
self.end = end
self.mpqa = mpqa.lookup(word, pos)
self.liwc = score_word(word)
self.pos = pos
self.word = word
self.index = index
self.rel = rel
self.lemma = lemma
def liwc(self):
if self._liwc is None:
self._liwc = dict(word_category_counter.score_word(self.text))
return self._liwc
