def arg_proc(self, id, point, sep):
self.a_predicates = []
if 'verbs' in point:
verbs = point['verbs']
for i, verb in verbs.iteritems():
i = '%s.%s'%(id, i)
(vt, vh) = verb['tokens']
if 'ARG' in verb:
args = verb['ARG']
for type,arg in args.items():
w_t = arg['wordform-t'].split()
w_h = arg['wordform-h'].split()
l_t = arg['lemma-t'].split()
l_h = arg['lemma-h'].split()
p_t = arg['pos-t'].split()
p_h = arg['pos-h'].split()
c_t = arg['chunk-t'].split()
c_h = arg['chunk-h'].split()
n_t = arg['ne-t'].split()
n_h = arg['ne-h'].split()
score = arg['score']
w_t.extend(w_h)
l_t.extend(l_h)
p_t.extend(p_h)
#TODO quit stop words
for j, word in enumerate(w_t):
word_arg = 'Token(%s, %s, "%s")'%(type, id, self.clean_str(word))
lemma_arg = 'Token(%s, %s, "%s")'%(type, id, self.clean_str(l_t[j]))
pos_arg = 'Token(%s, %s, "%s")'%(type, id, self.clean_str(p_t[j]))
lin = Lin()
sim_words = lin.expand_w(word)
wn = WNTools()
hyps = wn.get_mfs_hypernyms((l_t[j], p_t[j]))
self.a_predicates.append(word_arg)
self.a_predicates.append(lemma_arg)
self.a_predicates.append(pos_arg)
for sim_word in sim_words:
lin_arg = 'Token(%s, %s, "%s")'%(type, id, self.clean_str(sim_word))
self.a_predicates.append(lin_arg)
for key, tree in hyps:
t = 0
for category in tree:
if t >= 3:
break
hyp_arg = 'Token(%s, %s, "%s")'%(type, id, self.clean_str(category))
self.a_predicates.append(hyp_arg)
t +=1
arg_id = 'ARG(%s, %s, %s)'%(type, i, id)
self.a_predicates.append(arg_id)
return self.a_predicates
def arg_proc(self, id, point, sep):
self.a_predicates = []
n = 3 #levels in wn tree
if 'verbs' in point:
verbs = point['verbs']
for i, verb in verbs.iteritems():
i = '%s.%s'%(id, i)
(vt, vh) = verb['tokens']
if 'ARG' in verb:
args = verb['ARG']
for type,arg in args.items():
w_t = arg['wordform-t'].split()
w_h = arg['wordform-h'].split()
l_t = arg['lemma-t'].split()
l_h = arg['lemma-h'].split()
p_t = arg['pos-t'].split()
p_h = arg['pos-h'].split()
c_t = arg['chunk-t'].split()
c_h = arg['chunk-h'].split()
n_t = arg['ne-t'].split()
n_h = arg['ne-h'].split()
score = arg['score']
w_t.extend(w_h)
l_t.extend(l_h)
p_t.extend(p_h)
#TODO quit stop words
for j, word in enumerate(w_t):
word_arg = '>token_word\n"%s" %s "%s"'%(type, j, self.clean_str(word))
lemma_arg = '>token_lemma\n"%s" %s "%s"'%(type, j, self.clean_str(l_t[j]))
pos_arg = '>token_pos\n"%s" %s "%s"'%(type, j, self.clean_str(p_t[j]))
lin = Lin()
sim_words = lin.expand_w(word)
wn = WNTools()
hyps = wn.get_mfs_hypernyms((l_t[j], p_t[j]))
self.a_predicates.append(word_arg)
self.a_predicates.append(lemma_arg)
self.a_predicates.append(pos_arg)
for j, sim_word in enumerate(sim_words):
lin_arg = '>token_lin\n"%s" %s "%s"'%(type, j, self.clean_str(sim_word))
self.a_predicates.append(lin_arg)
for key, tree in hyps:
j = 0
for category in tree[:n]:
hyp_arg = '>token_wn\n"%s" %s "%s"'%(type, j, self.clean_str(category))
j += 1
self.a_predicates.append(hyp_arg)
arg_id = '>arg\n"%s" "%s%s%s" %s'%(type, self.clean_str(vt), sep, self.clean_str(vh), id)
self.a_predicates.append(arg_id)
return self.a_predicates
def main(args):
pickle_file = args[0]
print 'loading file:',pickle_file
with open(pickle_file, 'r') as pf:
pairs = pickle.load(pf)
k = 0
for pair in pairs:
print 'id:', pair.get_id()
print 's1:', pair.get_text()
print 's2:', pair.get_hypo()
print 'features:', pair.get_features_text_type()
print 'set-metrics, cos test'
lemmas_text = pair.get_feature_text('lemmas')
lemmas_hypo = pair.get_feature_hypo('lemmas')
set_th = SetMetrics(lemmas_text, lemmas_hypo)
cos = set_th.cosine()
#print cos
print 'SRL tools'
frames_text = pair.get_feature_text('frames')
print frames_text
print '################'
srl = SRLTools(lemmas_text, frames_text)
word_to_frame = srl.get_words_frame()
print word_to_frame
print '################'
print srl.get_verbs()
print '################'
#print 'verb-metrics, '
pos_text = pair.get_feature_text('pos')
pos_hypo = pair.get_feature_hypo('pos')
verbs = VerbMetrics()
lin = Lin()
vectors = VectorMetrics()
hyper = WNTools()
for i, pos_tuple_t in enumerate(pos_text):
(token, pos_t) = pos_tuple_t
if pos_t.startswith('V'):
for j, pos_tuple_h in enumerate(pos_hypo):
(token, pos_h) = pos_tuple_h
if pos_h.startswith('V'):
verbs.set_text_verb(lemmas_text[i])
verbs.set_hypo_verb(lemmas_hypo[j])
#print 'verbs test t:%s h:%s'%(lemmas_text[i], lemmas_hypo[j])
vn_isec = verbs.vn_isec()
#print 'verb net isec: %d'%vn_isec
#print 'lin(%s):'%lemmas_text[i], '\n', lin.n_similar_words(lemmas_text[i])
#print 'lin(%s):'%lemmas_hypo[j], '\n', lin.n_similar_words(lemmas_hypo[j])
t_sim = lin.n_similar_words(lemmas_text[i])
h_sim = lin.n_similar_words(lemmas_hypo[j])
t_score = [float(score) for word,score in t_sim]
h_score = [float(score) for word,score in h_sim]
vectors.set_vectors(t_score, h_score)
#print 'cos_vect: ', vectors.cosine()
elif pos_h.startswith('N'):
#print 'wn test hypernyms'
trees = hyper.get_mfs_hypernyms((lemmas_hypo[j], pos_h))
#print trees
k += 1
if k >= 10:
break
pf.close
return
def arg_proc(self, id, point, sep):
self.a_predicates = []
n = 3 #levels in wn tree
if 'verbs' in point:
verbs = point['verbs']
for i, verb in verbs.iteritems():
i = '%s.%s' % (id, i)
(vt, vh) = verb['tokens']
if 'ARG' in verb:
args = verb['ARG']
for type, arg in args.items():
w_t = arg['wordform-t'].split()
w_h = arg['wordform-h'].split()
l_t = arg['lemma-t'].split()
l_h = arg['lemma-h'].split()
p_t = arg['pos-t'].split()
p_h = arg['pos-h'].split()
c_t = arg['chunk-t'].split()
c_h = arg['chunk-h'].split()
n_t = arg['ne-t'].split()
n_h = arg['ne-h'].split()
score = arg['score']
w_t.extend(w_h)
l_t.extend(l_h)
p_t.extend(p_h)
#TODO quit stop words
for j, word in enumerate(w_t):
word_arg = '>token_word\n"%s" %s "%s"' % (
type, j, self.clean_str(word))
lemma_arg = '>token_lemma\n"%s" %s "%s"' % (
type, j, self.clean_str(l_t[j]))
pos_arg = '>token_pos\n"%s" %s "%s"' % (
type, j, self.clean_str(p_t[j]))
lin = Lin()
sim_words = lin.expand_w(word)
wn = WNTools()
hyps = wn.get_mfs_hypernyms((l_t[j], p_t[j]))
self.a_predicates.append(word_arg)
self.a_predicates.append(lemma_arg)
self.a_predicates.append(pos_arg)
for j, sim_word in enumerate(sim_words):
lin_arg = '>token_lin\n"%s" %s "%s"' % (
type, j, self.clean_str(sim_word))
self.a_predicates.append(lin_arg)
for key, tree in hyps:
j = 0
for category in tree[:n]:
hyp_arg = '>token_wn\n"%s" %s "%s"' % (
type, j, self.clean_str(category))
j += 1
self.a_predicates.append(hyp_arg)
arg_id = '>arg\n"%s" "%s%s%s" %s' % (
type, self.clean_str(vt), sep, self.clean_str(vh),
id)
self.a_predicates.append(arg_id)
return self.a_predicates