def optimise_determiner(phrase, np_phrases, context):
"""Select the approrpiate determiner. """
get_log().debug('Fixing determiners: {}'.format(phrase))
if (not isinstance(phrase, NounPhrase)):
get_log().debug('...not an NP')
return phrase
get_log().debug('NPs: {}'
.format(' '.join([str(x) for x in np_phrases])))
# FIXME: this whould look at all modifiers
distractors = [x for x in np_phrases
if (hasattr(x, 'head') and
hasattr(phrase, 'head') and phrase.head == x.head)]
get_log().debug('distractors: {}'
.format(' '.join([str(x) for x in distractors])))
if (phrase.head.has_feature('PROPER', 'true') or
phrase.head.has_feature('cat', 'PRONOUN')):
get_log().debug('...proper or pronoun')
phrase.spec = Element()
elif (not phrase.head.has_feature('cat', 'PRONOUN') and
phrase in distractors[-1:] and
len(distractors) == 1):
get_log().debug('...unpronominalised phrase that is last mentioned')
phrase.spec = Word('the', 'DETERMINER')
elif (lexicon.guess_phrase_number(phrase) != Number.plural and
not phrase.head.has_feature('cat', 'PRONOUN')):
get_log().debug('...indefinite')
if phrase.head.string and phrase.head.string[0] in "aeiouy":
phrase.spec = Word('an', 'DETERMINER')
else:
phrase.spec = Word('a', 'DETERMINER')
return phrase
def optimise_ref_exp(phrase, context):
"""Replace anaphoric noun phrases with pronouns when possible. """
# TODO: include Number in the dicision process (it vs they)
# FIXME: Coordinated elements need some special attention
result = copy(phrase)
# test for selecting phrases taht can be processed
test = lambda x: isinstance(x, NounPhrase) or isinstance(x, Coordination)
# reverse so that we start with large phrases first (eg CC)
get_log().debug('-='*40)
get_log().debug('constituents:')
for x in phrase.constituents():
get_log().debug('\t {}'.format(' '.join(repr(x).split())))
nps = [x for x in phrase.constituents() if test(x)]
uttered = []
processed_ids = set()
for np in nps:
replaced = False
get_log().debug('current NP:\n{}'.format(np))
gender = lexicon.guess_phrase_gender(np)
get_log().debug('gender of NP: {}'.format(gender))
number = lexicon.guess_phrase_number(np)
get_log().debug('number of NP: {}'.format(number))
if not np.has_feature('PERSON'):
if context.is_last_speaker(np):
person = Person.first
else:
person = Person.third
else:
person = ('PERSON', np.get_feature('PERSON'))
phrases = [x for x in (context.np_stack + uttered)
if lexicon.guess_phrase_gender(x) == gender]
# get_log().debug('distractors of NP:\n\t{}'.format(distractors))
if id(np) in processed_ids:
get_log().debug('current NP: {} was already processed'.format(np))
continue
# if ((np in context.np_stack or np in uttered) and np == phrases[-1]):
if (np in phrases[-1:]):
# this np is the most salient so pronominalise it
if isinstance(phrase, Clause):
if id(np) == id(phrase.subj):
pronoun = pronominalise(np, gender, PronounUse.subjective, person)
elif (np in phrase.subj.constituents() and
np in phrase.vp.constituents()):
pronoun = pronominalise(np, gender, PronounUse.reflexive, person)
# TODO: implement -- possessive will be used if it is a complement of an NP?
# elif any(id(np) in [id(x) for x in pp.constituents()]
# for pp in pps):
# pronoun = pronominalise(np, gender, PronounUse.possessive)
elif (np in phrase.vp.constituents()):
pronoun = pronominalise(np, gender, PronounUse.objective, person)
else:
pronoun = pronominalise(np, gender, PronounUse.subjective, person)
else:
pronoun = pronominalise(np, gender, PronounUse.subjective, person)
get_log().debug('replacing {}:{} with {}'.format(id(np), np, pronoun))
replace_element_with_id(result, id(np), pronoun)
replaced = True
# if you replace an element, remove all the subphrases from the list
processed = [y for y in np.constituents()]
processed_ids.update([id(x) for x in processed])
unspec_np = deepcopy(np)
unspec_np.spec = Element()
uttered.append(unspec_np)
if not replaced:
# fix determiners in the processed NP
optimise_determiner(np, phrases, context)
context.add_sentence(phrase)
return result
