def generate_sentence(loc, consistent, scene=None, speaker=None):
utils.scene = utils.ModelScene(scene, speaker)
(lmk, lmk_prob, lmk_ent), (rel, rel_prob, rel_ent) = get_meaning(loc=loc)
meaning1 = m2s(lmk, rel)
logger(meaning1)
while True:
rel_exp_chain, rele_prob_chain, rele_ent_chain, rel_terminals, rel_landmarks = get_expansion(
'RELATION', rel=rel)
lmk_exp_chain, lmke_prob_chain, lmke_ent_chain, lmk_terminals, lmk_landmarks = get_expansion(
'LANDMARK-PHRASE', lmk=lmk)
rel_words, relw_prob, relw_ent, rel_a = get_words(
rel_terminals, landmarks=rel_landmarks, rel=rel)
lmk_words, lmkw_prob, lmkw_ent, lmk_a = get_words(
lmk_terminals,
landmarks=lmk_landmarks,
prevword=(rel_words[-1] if rel_words else None))
sentence = ' '.join(rel_words + lmk_words)
logger('rel_exp_chain: %s' % rel_exp_chain)
logger('lmk_exp_chain: %s' % lmk_exp_chain)
meaning = Meaning(
(lmk, lmk_prob, lmk_ent, rel, rel_prob, rel_ent, rel_exp_chain,
rele_prob_chain, rele_ent_chain, rel_terminals, rel_landmarks,
lmk_exp_chain, lmke_prob_chain, lmke_ent_chain, lmk_terminals,
lmk_landmarks, rel_words, relw_prob, relw_ent, lmk_words,
lmkw_prob, lmkw_ent))
meaning.rel_a = rel_a
meaning.lmk_a = lmk_a
if consistent:
# get the most likely meaning for the generated sentence
try:
posteriors = get_sentence_posteriors(sentence,
iterations=10,
extra_meaning=(lmk, rel))
except:
print 'try again ...'
continue
meaning2 = max(posteriors, key=itemgetter(1))[0]
# is the original meaning the best one?
if meaning1 != meaning2:
print
print 'sentence:', sentence
print 'original:', meaning1
print 'interpreted:', meaning2
print 'try again ...'
print
continue
for m, p in sorted(posteriors, key=itemgetter(1)):
print m, p
return meaning, sentence
def generate_sentence(loc, consistent, scene=None, speaker=None, usebest=False, golden=False, meaning=None, printing=True):
utils.scene = utils.ModelScene(scene, speaker)
if meaning is None:
(lmk, lmk_prob, lmk_ent), (rel, rel_prob, rel_ent) = get_meaning(loc=loc, usebest=usebest)
else:
lmk, rel = meaning
lmk_prob = lmk_ent = rel_prob = rel_ent = None
meaning1 = m2s(lmk, rel)
logger( meaning1 )
while True:
rel_exp_chain, rele_prob_chain, rele_ent_chain, rel_terminals, rel_landmarks = get_expansion('RELATION', rel=rel, usebest=usebest, golden=golden, printing=printing)
lmk_exp_chain, lmke_prob_chain, lmke_ent_chain, lmk_terminals, lmk_landmarks = get_expansion('LANDMARK-PHRASE', lmk=lmk, usebest=usebest, golden=golden, printing=printing)
rel_words, relw_prob, relw_ent, rel_a = get_words(rel_terminals, landmarks=rel_landmarks, rel=rel, usebest=usebest, golden=golden, printing=printing)
lmk_words, lmkw_prob, lmkw_ent, lmk_a = get_words(lmk_terminals, landmarks=lmk_landmarks, prevword=(rel_words[-1] if rel_words else None), usebest=usebest, golden=golden, printing=printing)
sentence = ' '.join(rel_words + lmk_words)
if printing: logger( 'rel_exp_chain: %s' % rel_exp_chain )
if printing: logger( 'lmk_exp_chain: %s' % lmk_exp_chain )
meaning = Meaning((lmk, lmk_prob, lmk_ent,
rel, rel_prob, rel_ent,
rel_exp_chain, rele_prob_chain, rele_ent_chain, rel_terminals, rel_landmarks,
lmk_exp_chain, lmke_prob_chain, lmke_ent_chain, lmk_terminals, lmk_landmarks,
rel_words, relw_prob, relw_ent,
lmk_words, lmkw_prob, lmkw_ent))
meaning.rel_a = rel_a
meaning.lmk_a = lmk_a
if consistent:
# get the most likely meaning for the generated sentence
try:
posteriors = get_sentence_posteriors(sentence, iterations=10, extra_meaning=(lmk,rel))
except:
print 'try again ...'
continue
meaning2 = max(posteriors, key=itemgetter(1))[0]
# is the original meaning the best one?
if meaning1 != meaning2:
print
print 'sentence:', sentence
print 'original:', meaning1
print 'interpreted:', meaning2
print 'try again ...'
print
continue
for m,p in sorted(posteriors, key=itemgetter(1)):
print m, p
return meaning, sentence
def generate_sentence(loc, consistent):
while True:
lmk, rel = get_meaning(loc=loc)
print m2s(lmk, rel)
rel_exp, rel_prob, rel_ent = get_expansion('RELATION', rel=rel)
lmk_exp, lmk_prob, lmk_ent = get_expansion('LANDMARK-PHRASE', lmk=lmk)
rel_words, relw_prob, relw_ent = get_words(rel_exp, 'RELATION', rel=rel)
lmk_words, lmkw_prob, lmkw_ent = get_words(lmk_exp, 'LANDMARK-PHRASE', lmk=lmk)
sentence = ' '.join(rel_words + lmk_words)
if consistent:
meaning1 = m2s(lmk,rel)
# get the most likely meaning for the generated sentence
posteriors = get_sentence_posteriors(sentence)
meaning2 = max(posteriors, key=itemgetter(1))[0]
# is this what we are trying to say?
if meaning1 != meaning2:
continue
return sentence
