def __init__(self):
self.builder = StatementBuilder()
self.adder = StatementSafeAdder()
self.question_handler = QuestionHandler()
self.sfactory = SentenceFactory()
self.output_sentence = []
def __init__(self):
self.builder = StatementBuilder()
self.adder = StatementSafeAdder()
self.question_handler = QuestionHandler()
self.sfactory = SentenceFactory()
self.output_sentence = []
class ContentAnalyser(object):
def __init__(self):
self.builder = StatementBuilder()
self.adder = StatementSafeAdder()
self.question_handler = QuestionHandler()
self.sfactory = SentenceFactory()
self.output_sentence = []
def analyse(self, sentence, current_speaker):
"""Analyse a sentence intent and perform the corresponding behaviour.
:returns: a pair with
- a list of symbolic statements produced
during the analyse. Note that these statements have
already been sent to the knowledge base
- a situation ID that identifies a situation the speaker is
desiring (for an imperative sentence or an order) or
experiencing (like an 'InterrogativeState' for a question).
These two values can be None.
Note also that an answer to the speaker is stored in self.output_sentence
after analyse() completes.
It can be used to tell the human to acknowledge an order, answer a
gratulation, the answer a question (or the fact the answer is not known),
etc.
"""
self.builder.clear_all()
self.output_sentence = []
sentence = self.pre_analyse_content(sentence)
if sentence.data_type == [INTERJECTION, EXCLAMATION]:
pass
if sentence.data_type in [START, END]:
self.output_sentence.append(sentence)
if sentence.data_type == GRATULATION:
self.output_sentence.extend(
self.sfactory.create_gratulation_reply())
if sentence.data_type in [AGREEMENT, DISAGREEMENT]:
self.output_sentence.extend(self.sfactory.create_agree_reply())
if sentence.data_type in [IMPERATIVE, STATEMENT]:
logger.debug(
colored_print(
"Processing the content of " +
("an imperative sentence" if sentence.data_type
== IMPERATIVE else "a statement "), "magenta"))
return self.process_sentence(sentence, current_speaker)
if sentence.data_type in [W_QUESTION, YES_NO_QUESTION]:
logger.debug(
colored_print(
"Processing the content of " +
("a W question " if sentence.data_type == W_QUESTION else
"a YES/NO question"), "magenta"))
return self.process_question(sentence, current_speaker)
return None, None # default: no statement generated, no situation ID
def process_sentence(self, sentence, current_speaker):
self.builder.set_current_speaker(current_speaker)
stmts, situation_id = self.builder.process_sentence(sentence)
if stmts:
self.add_stmts(stmts)
emotions.satisfied()
if situation_id:
# If a new situation has been created, mark it as
# active.
self.output_sentence.extend(self.sfactory.create_agree_reply())
ResourcePool().mark_active(situation_id)
else:
logger.info("No statements produced")
# Class grounding
if self.builder.lear_more_concept:
self.output_sentence.extend(
self.sfactory.create_what_is_a_reference(
sentence, self.builder.lear_more_concept))
return stmts, situation_id
def process_question(self, sentence, current_speaker):
self.question_handler.set_current_speaker(current_speaker)
# 'stmts' contains a list of statement describing the current
# 'interrogative state' of the interactor.
answer, stmts, situation_id = self.question_handler.process_sentence(
sentence)
if stmts:
self.add_stmts(stmts)
else:
logger.info("No statements produced")
if answer:
emotions.satisfied()
logger.info(
level_marker(level=2, color="yellow") + "Found: \n" +
colored_print(str(answer), None, "magenta"))
else:
emotions.sorry()
logger.info(
level_marker(level=2, color="yellow") +
"Couldn't find anything!")
if sentence.data_type == W_QUESTION:
self.output_sentence.extend(
self.sfactory.create_w_question_answer(
sentence, answer, self.question_handler._current_speaker,
self.question_handler.get_query_on_field()))
if sentence.data_type == YES_NO_QUESTION:
self.output_sentence.extend(
self.sfactory.create_yes_no_answer(sentence, answer))
return stmts, situation_id
def add_stmts(self, stmts):
logger.info("Generated statements: ")
for s in stmts:
logger.info(">> " + colored_print(s, None, 'magenta'))
self.adder._current_speaker = self.builder._current_speaker
self.adder._unclarified_ids = self.builder._unclarified_ids
self.adder._statements = stmts
self.adder._statements_to_remove = self.builder._statements_to_remove
stmts = self.adder.process()
logger.debug("...added to the ontology")
def analyse_output(self):
return self.output_sentence
def pre_analyse_content(self, sentence):
""" this method analyse the content of a sentence and possibly changes its purpose.
E.g: Can you give me the bottle?
The sentence above is of YES_NO_QUESTION type but should actually
be processed as an order in which the current speaker desires 'the
bottle'. Therefore, we turn it into 'give me the bottle'.
"""
# Case of :
# -INPUT: Yes_no_question + can + action verb
# -OUTPUT: Imperative + action verb
#
if sentence.data_type == YES_NO_QUESTION:
for sv in sentence.sv:
for verb in sv.vrb_main:
if 'can+' in verb:
vrb_main = verb.lstrip('can+')
if not vrb_main in ResourcePool().state + ResourcePool(
).action_verb_with_passive_behaviour.keys(
) + ResourcePool().goal_verbs:
logger.debug(
colored_print(
"Interpreting the <can + action verb> sequence as a desire.\nApplying transformation:",
"magenta"))
sv.vrb_main[sv.vrb_main.index(verb)] = verb.lstrip(
'can+')
sentence.data_type = IMPERATIVE
logger.debug(str(sentence))
return sentence
return sentence
class ContentAnalyser(object):
def __init__(self):
self.builder = StatementBuilder()
self.adder = StatementSafeAdder()
self.question_handler = QuestionHandler()
self.sfactory = SentenceFactory()
self.output_sentence = []
def analyse(self, sentence, current_speaker):
"""Analyse a sentence intent and perform the corresponding behaviour.
:returns: a pair with
- a list of symbolic statements produced
during the analyse. Note that these statements have
already been sent to the knowledge base
- a situation ID that identifies a situation the speaker is
desiring (for an imperative sentence or an order) or
experiencing (like an 'InterrogativeState' for a question).
These two values can be None.
Note also that an answer to the speaker is stored in self.output_sentence
after analyse() completes.
It can be used to tell the human to acknowledge an order, answer a
gratulation, the answer a question (or the fact the answer is not known),
etc.
"""
self.builder.clear_all()
self.output_sentence = []
sentence = self.pre_analyse_content(sentence)
if sentence.data_type == [INTERJECTION, EXCLAMATION]:
pass
if sentence.data_type in [START, END]:
self.output_sentence.append(sentence)
if sentence.data_type == GRATULATION:
self.output_sentence.extend(self.sfactory.create_gratulation_reply())
if sentence.data_type in [AGREEMENT, DISAGREEMENT]:
self.output_sentence.extend(self.sfactory.create_agree_reply())
if sentence.data_type in [IMPERATIVE, STATEMENT]:
logger.debug(colored_print("Processing the content of " + (
"an imperative sentence" if sentence.data_type == IMPERATIVE else "a statement "), "magenta"))
return self.process_sentence(sentence, current_speaker)
if sentence.data_type in [W_QUESTION, YES_NO_QUESTION]:
logger.debug(colored_print("Processing the content of " + (
"a W question " if sentence.data_type == W_QUESTION else "a YES/NO question"), "magenta"))
return self.process_question(sentence, current_speaker)
return None, None # default: no statement generated, no situation ID
def process_sentence(self, sentence, current_speaker):
self.builder.set_current_speaker(current_speaker)
stmts, situation_id = self.builder.process_sentence(sentence)
if stmts:
self.add_stmts(stmts)
emotions.satisfied()
if situation_id:
# If a new situation has been created, mark it as
# active.
self.output_sentence.extend(self.sfactory.create_agree_reply())
ResourcePool().mark_active(situation_id)
else:
logger.info("No statements produced")
# Class grounding
if self.builder.lear_more_concept:
self.output_sentence.extend(
self.sfactory.create_what_is_a_reference(sentence, self.builder.lear_more_concept))
return stmts, situation_id
def process_question(self, sentence, current_speaker):
self.question_handler.set_current_speaker(current_speaker)
# 'stmts' contains a list of statement describing the current
# 'interrogative state' of the interactor.
answer, stmts, situation_id = self.question_handler.process_sentence(sentence)
if stmts:
self.add_stmts(stmts)
else:
logger.info("No statements produced")
if answer:
emotions.satisfied()
logger.info(
level_marker(level=2, color="yellow") + "Found: \n" + colored_print(str(answer), None, "magenta"))
else:
emotions.sorry()
logger.info(level_marker(level=2, color="yellow") + "Couldn't find anything!")
if sentence.data_type == W_QUESTION:
self.output_sentence.extend(self.sfactory.create_w_question_answer(sentence,
answer,
self.question_handler._current_speaker,
self.question_handler.get_query_on_field()))
if sentence.data_type == YES_NO_QUESTION:
self.output_sentence.extend(self.sfactory.create_yes_no_answer(sentence, answer))
return stmts, situation_id
def add_stmts(self, stmts):
logger.info("Generated statements: ")
for s in stmts:
logger.info(">> " + colored_print(s, None, 'magenta'))
self.adder._current_speaker = self.builder._current_speaker
self.adder._unclarified_ids = self.builder._unclarified_ids
self.adder._statements = stmts
self.adder._statements_to_remove = self.builder._statements_to_remove
stmts = self.adder.process()
logger.debug("...added to the ontology")
def analyse_output(self):
return self.output_sentence
def pre_analyse_content(self, sentence):
""" this method analyse the content of a sentence and possibly changes its purpose.
E.g: Can you give me the bottle?
The sentence above is of YES_NO_QUESTION type but should actually
be processed as an order in which the current speaker desires 'the
bottle'. Therefore, we turn it into 'give me the bottle'.
"""
# Case of :
# -INPUT: Yes_no_question + can + action verb
# -OUTPUT: Imperative + action verb
#
if sentence.data_type == YES_NO_QUESTION:
for sv in sentence.sv:
for verb in sv.vrb_main:
if 'can+' in verb:
vrb_main = verb.lstrip('can+')
if not vrb_main in ResourcePool().state + ResourcePool().action_verb_with_passive_behaviour.keys() + ResourcePool().goal_verbs:
logger.debug(colored_print(
"Interpreting the <can + action verb> sequence as a desire.\nApplying transformation:",
"magenta"))
sv.vrb_main[sv.vrb_main.index(verb)] = verb.lstrip('can+')
sentence.data_type = IMPERATIVE
logger.debug(str(sentence))
return sentence
return sentence
