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 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 __str__(self):
res = level_marker() + pprint(self.data_type, SENTENCE_TYPE)
res += pprint(self.aim, SENTENCE_AIM) # 'aim' may be None
if self.sn:
sn = ""
for s in self.sn:
sn = str(s).replace("\n", "\n\t") + "\n"
res += pprint(sn, SUBJECT)
if self.sv:
for s in self.sv:
res += str(s).replace("\n", "\n\t") + "\n"
#res += "This sentence is " + ("fully resolved." if self.resolved() else "not fully resolved.")
if self.isvalid():
res = pprint(res, SENTENCE)
else:
res = pprint(res, AGRAMMATICAL_SENTENCE)
return res
def __str__(self):
res = level_marker() + pprint(self.data_type, SENTENCE_TYPE)
res += pprint(self.aim, SENTENCE_AIM) # 'aim' may be None
if self.sn:
sn = ""
for s in self.sn:
sn = str(s).replace("\n", "\n\t") + "\n"
res += pprint(sn, SUBJECT)
if self.sv:
for s in self.sv:
res += str(s).replace("\n", "\n\t") + "\n"
#res += "This sentence is " + ("fully resolved." if self.resolved() else "not fully resolved.")
if self.isvalid():
res = pprint(res, SENTENCE)
else:
res = pprint(res, AGRAMMATICAL_SENTENCE)
return res
def __str__(self):
res = level_marker()
if self._conjunction != 'AND':
res += pprint(self._conjunction, CONJUNCTION)
if self._quantifier != 'ONE':
res += pprint(self._quantifier, QUANTIFIER)
if self._resolved:
res += pprint(self.id, ID)
res = pprint(res, RESOLVED)
else:
if self.det:
res += pprint(" ".join(self.det), DETERMINER)
for k in self.adj:
if k[1]:
res += pprint(" ".join(k[1]), ADJECTIVE_QUALIFIER)
res += pprint(k[0], ADJECTIVE)
if self.noun:
res += pprint(", ".join(self.noun), NOUN)
if self.noun_cmpl:
for s in self.noun_cmpl:
res += pprint(str(s).replace("\n", "\n\t"), NOUN_CMPLT)
if self.relative:
for rel in self.relative:
res += pprint(str(rel).replace("\n", "\n\t"), RELATIVE_GRP)
return pprint(res, NOMINAL_GROUP)
def __str__(self):
res = level_marker()
if self._conjunction != 'AND':
res += pprint(self._conjunction, CONJUNCTION)
if self._quantifier != 'ONE':
res += pprint(self._quantifier, QUANTIFIER)
if self._resolved:
res += pprint(self.id, ID)
res = pprint(res, RESOLVED)
else:
if self.det:
res += pprint(" ".join(self.det), DETERMINER)
for k in self.adj:
if k[1]:
res += pprint(" ".join(k[1]), ADJECTIVE_QUALIFIER)
res += pprint(k[0], ADJECTIVE)
if self.noun:
res += pprint(", ".join(self.noun), NOUN)
if self.noun_cmpl:
for s in self.noun_cmpl:
res += pprint(str(s).replace("\n", "\n\t"), NOUN_CMPLT)
if self.relative:
for rel in self.relative:
res += pprint(str(rel).replace("\n", "\n\t"), RELATIVE_GRP)
return pprint(res, NOMINAL_GROUP)
def process_sentence(self, sentence):
"""This processes a w_question or yes_no_question sentence"""
self._sentence = sentence
#StatementBuilder
builder = StatementBuilder(self._current_speaker)
self._statements, situation_id = builder.process_sentence(
self._sentence)
logger.info(
level_marker(level=2, color="yellow") +
"Generated statements based on the sentence components: " +
colored_print(str(self._statements), None, "magenta"))
#Case the question is a y_n_question : check the fact in the ontology
if sentence.data_type == YES_NO_QUESTION:
self._statements = self._set_situation_id(self._statements)
logger.info(
level_marker(level=2, color="yellow") +
"Generated statements for this question: " +
colored_print(str(self._statements), None, "magenta"))
#Processing :Do you know something?
if self.process_on_knowing_concept:
#self._statements = [agent knows object]
for s in self._statements:
self._answer = True
if "knows" in s:
[agent, object] = s.split(" knows ")
onto_lookup = []
logger.debug(
level_marker(level=2, color="yellow") +
"Looking up for " + object + " in " + agent +
"'s model")
onto_lookup = ResourcePool(
).ontology_server.lookupForAgent(
ResourcePool().get_model_mapping(agent), object)
self._answer = self._answer and (True if onto_lookup
else False)
self.process_on_knowing_concept = False
else:
logger.debug(
level_marker(level=2, color="yellow") +
"Checking in the ontology: " +
colored_print(str(self._statements), None, "magenta"))
self._answer = ResourcePool().ontology_server.check(
self._statements)
#Case the question is a w_question : find the concept the concept that answers the question
if sentence.data_type == W_QUESTION:
#
self._query_on_field = self._set_query_on_field(sentence)
statements_with_bound_tokens = self._remove_statements_with_no_unbound_tokens(
self._statements)
#Agent from which the ontology model is queried
agent = self._default_agent
self._answer = []
#For all the possible subjects of a same question
if not self._sentence.sn:
statements_to_query = [
self._extend_statement_from_sentence_aim(
statements_with_bound_tokens)
]
else:
statements_to_query = [
self._extend_statement_from_sentence_aim(
statements_with_bound_tokens, sn)
for sn in self._sentence.sn
]
for statements in statements_to_query:
if self.process_on_knowing_concept:
#Get agent in a statement such as [agent knows object]
for s in statements:
if "knows" in s:
[agent, object] = s.split(" knows ")
break
#No need of statements such as [S knows O]
[statements.remove(s) for s in statements if "knows" in s]
self.process_on_knowing_concept = False
if statements:
logger.info(
level_marker(level=2, color="yellow") +
"Generated statements for this question: " +
colored_print(str(self._statements), None, "magenta"))
answers = []
if self._process_on_location:
prepositions_list = ResourcePool(
).preposition_rdf_object_property.copy()
roles = dict([(preposition, prepositions_list[preposition][0]) \
for preposition in prepositions_list.keys() \
if 'objectFoundInLocation' in prepositions_list[preposition]])
#Case of ojectFound in location
stmts = []
prepositions_already_used = []
for role in roles:
if roles[role] in prepositions_already_used:
continue
stmts = [
s.replace('objectFoundInLocation', roles[role])
for s in statements
]
logger.debug(
level_marker(level=2, color="yellow") +
"Searching in " + agent + " model: " +
colored_print(str(stmts), None, "magenta"))
answers = ResourcePool(
).ontology_server.findForAgent(
ResourcePool().get_model_mapping(agent),
'?concept', stmts)
prepositions_already_used.append(roles[role])
if answers:
ResourcePool().mark_active(answers)
self._answer.append([[role], answers])
#Case of object found in location + direction
stmts = [
s.replace('objectFoundInLocation', 'isAt')
for s in statements
]
for role in ResourcePool().direction_words:
logger.debug(
level_marker(level=2, color="yellow") +
"Searching in " + agent + " model: " +
colored_print(
str(stmts + [
'?concept is' + role.capitalize() +
'Of ?obj', '?concept rdf:type Location'
]), None, "magenta"))
answers = ResourcePool(
).ontology_server.findForAgent(
ResourcePool().get_model_mapping(agent),
'?obj', stmts + [
'?concept is' + role.capitalize() +
'Of ?obj', '?concept rdf:type Location'
])
if answers:
ResourcePool().mark_active(answers)
self._answer.append([[role], answers])
else:
logger.debug(
level_marker(level=2, color="yellow") +
"Searching in " + agent + " model: " +
colored_print(str(statements), None, "magenta"))
answers = ResourcePool().ontology_server.findForAgent(
ResourcePool().get_model_mapping(agent),
'?concept', statements)
if answers:
ResourcePool().mark_active(answers)
self._answer.append([[], answers])
else:
pass
self._statements.extend(statements)
stmts, sit_id = self._build_situation_statements()
return self._answer, stmts, sit_id
def process_sentence(self, sentence):
"""This processes a w_question or yes_no_question sentence"""
self._sentence = sentence
#StatementBuilder
builder = StatementBuilder(self._current_speaker)
self._statements, situation_id = builder.process_sentence(self._sentence)
logger.info(level_marker(level=2,
color="yellow") + "Generated statements based on the sentence components: " + colored_print(
str(self._statements), None, "magenta"))
#Case the question is a y_n_question : check the fact in the ontology
if sentence.data_type == YES_NO_QUESTION:
self._statements = self._set_situation_id(self._statements)
logger.info(
level_marker(level=2, color="yellow") + "Generated statements for this question: " + colored_print(
str(self._statements), None, "magenta"))
#Processing :Do you know something?
if self.process_on_knowing_concept:
#self._statements = [agent knows object]
for s in self._statements:
self._answer = True
if "knows" in s:
[agent, object] = s.split(" knows ")
onto_lookup = []
try:
logger.debug(level_marker(level=2,
color="yellow") + "Looking up for " + object + " in " + agent + "'s model")
onto_lookup = ResourcePool().ontology_server.lookupForAgent(agent, object)
except AttributeError:
pass
self._answer = self._answer and (True if onto_lookup else False)
self.process_on_knowing_concept = False
else:
try:
logger.debug(level_marker(level=2, color="yellow") + "Checking in the ontology: " + colored_print(
str(self._statements), None, "magenta"))
self._answer = ResourcePool().ontology_server.check(self._statements)
except AttributeError: #the ontology server is not started of doesn't know the method
pass
#Case the question is a w_question : find the concept the concept that answers the question
if sentence.data_type == W_QUESTION:
#
self._query_on_field = self._set_query_on_field(sentence)
statements_with_bound_tokens = self._remove_statements_with_no_unbound_tokens(self._statements)
#Agent from which the ontology model is queried
agent = self._default_agent
self._answer = []
#For all the possible subjects of a same question
if not self._sentence.sn:
statements_to_query = [self._extend_statement_from_sentence_aim(statements_with_bound_tokens)]
else:
statements_to_query = [self._extend_statement_from_sentence_aim(statements_with_bound_tokens, sn) for sn
in self._sentence.sn]
for statements in statements_to_query:
if self.process_on_knowing_concept:
#Get agent in a statement such as [agent knows object]
for s in statements:
if "knows" in s:
[agent, object] = s.split(" knows ")
break
#No need of statements such as [S knows O]
[statements.remove(s) for s in statements if "knows" in s]
self.process_on_knowing_concept = False
if statements:
logger.info(level_marker(level=2,
color="yellow") + "Generated statements for this question: " + colored_print(
str(self._statements), None, "magenta"))
answers = []
if self._process_on_location:
prepositions_list = ResourcePool().preposition_rdf_object_property.copy()
roles = dict([(preposition, prepositions_list[preposition][0]) \
for preposition in prepositions_list.keys() \
if 'objectFoundInLocation' in prepositions_list[preposition]])
#Case of ojectFound in location
stmts = []
prepositions_already_used = []
for role in roles:
if roles[role] in prepositions_already_used:
continue
stmts = [s.replace('objectFoundInLocation', roles[role]) for s in statements]
try:
logger.debug(level_marker(level=2,
color="yellow") + "Searching in " + agent + " model: " + colored_print(
str(stmts), None, "magenta"))
answers = ResourcePool().ontology_server.findForAgent(agent, '?concept', stmts)
except AttributeError: #the ontology server is not started of doesn't know the method
pass
prepositions_already_used.append(roles[role])
if answers:
ResourcePool().mark_active(answers)
self._answer.append([[role], answers])
#Case of object found in location + direction
stmts = [s.replace('objectFoundInLocation', 'isAt') for s in statements]
for role in ResourcePool().direction_words:
try:
logger.debug(level_marker(level=2,
color="yellow") + "Searching in " + agent + " model: " + colored_print(
str(stmts + ['?concept is' + role.capitalize() + 'Of ?obj',
'?concept rdf:type Location']), None, "magenta"))
answers = ResourcePool().ontology_server.findForAgent(agent, '?obj', stmts + [
'?concept is' + role.capitalize() + 'Of ?obj', '?concept rdf:type Location'])
except AttributeError: #the ontology server is not started of doesn't know the method
pass
if answers:
ResourcePool().mark_active(answers)
self._answer.append([[role], answers])
else:
try:
logger.debug(level_marker(level=2,
color="yellow") + "Searching in " + agent + " model: " + colored_print(
str(statements), None, "magenta"))
answers = ResourcePool().ontology_server.findForAgent(agent, '?concept', statements)
except AttributeError: #the ontology server is not started of doesn't know the method
pass
if answers:
ResourcePool().mark_active(answers)
self._answer.append([[], answers])
else:
pass
self._statements.extend(statements)
stmts, sit_id = self._build_situation_statements()
return self._answer, stmts, sit_id
