def _send_state(state):
models = [ResourcePool().default_model]
policy = {"method": "add", "models": models}
state_id = generate_id(False)
statements = [
state_id + " rdf:type " + state, "myself experiences " + state_id
]
logger.info(colored_print("Setting my mood to " + state, "magenta"))
#logger.warning(colored_print("Not setting my mood due to Pellet bugs!", "magenta"))
ResourcePool().ontology_server.revise(statements, policy)
def _send_state(state):
models = [ResourcePool().default_model]
policy = {"method": "add", "models": models}
state_id = generate_id(False)
statements = [state_id + " rdf:type " + state,
"myself experiences " + state_id]
try:
logger.info(colored_print("Setting my mood to " + state, "magenta"))
#logger.warning(colored_print("Not setting my mood due to Pellet bugs!", "magenta"))
ResourcePool().ontology_server.revise(statements, policy)
except AttributeError: #the ontology server is not started of doesn't know the method
pass
def process_adjectives(self, nominal_group, ng_id, negative_object):
"""For any adjectives, we add it in the ontology with the objectProperty
'hasFeature' except if a specific category has been specified in the
adjectives list.
"""
for adj in nominal_group.adj:
# Case of 'other'
# E.g: the other cube:
if adj[0].lower() == "other":
self.process_on_other = True
pass
#self._statements.append(ng_id + " owl:differentFrom " + nominal_group.id)
elif adj[0].lower() == "same":
pass
#TODO: case of class Feature
# Apple are yellow fruits
# Case of features
else:
#Getting the object property if there exists a specific class
object_property = ''
try:
object_property = " has" + ResourcePool().adjectives[adj[0]] + " "
#Default case, creating hasFeature object Property
except KeyError:
object_property = " hasFeature "
#Case negative assertion
if negative_object:
negative_adj = generate_id(with_question_mark=not nominal_group._resolved)
self._statements.append(ng_id + object_property + negative_adj)
self._statements.append(negative_adj + ' owl:differentFrom ' + adj[0])
#Case Affirmative assertion
else:
if isinstance(ng_id, basestring):
ng_id = [ng_id]
self._statements += [id + object_property + adj[0] for id in ng_id]
def set_nominal_group_id(self, ng):
if ng.id:
return ng.id
onto = ResourcePool().ontology_server.lookupForAgent(
ResourcePool().get_model_mapping(self._current_speaker), ng.noun[0])
if onto:
for c in onto:
if "instance" in c:
return c[0]
if ng.noun[0].lower() in ['i', 'me']:
return self._current_speaker
if ng.noun[0].lower() == 'you':
return 'myself'
id = generate_id()
self._unclarified_ids.append(id)
return id
def set_nominal_group_id(self, ng):
if ng.id:
return ng.id
onto = ''
try:
onto = ResourcePool().ontology_server.lookupForAgent(self._current_speaker, ng.noun[0])
except AttributeError: #the ontology server is not started of doesn't know the method
pass
if onto:
for c in onto:
if "INSTANCE" in c:
return c[0]
if ng.noun[0].lower() in ['i', 'me']:
return self._current_speaker
if ng.noun[0].lower() == 'you':
return 'myself'
id = generate_id()
self._unclarified_ids.append(id)
return id
def process_sentence_adverb(self, verbal_group):
id = generate_id(with_question_mark=False)
for a in verbal_group.advrb:
if a in ResourcePool().location_adverbs:
self._statements += ["%s hasGoal %s" % (self.situation_id, id),
"%s rdf:type %sZone" % (id, a.capitalize())]
def process_indirect_complement(self, indirect_cmpls, verb, sit_id):
for ic in indirect_cmpls:
# Case 1: if there is no preposition, the indirect complement is obviously an indirect object.
# Therefore, it receives the action
# e.g. I gave you a ball also means I gave a ball 'to' you
# see http://www.englishlanguageguide.com/english/grammar/indirect-object.asp
#Case 2: if there is a preposition, the indirect complement is either an indirect object or an adverbial
# if the main verb is specified as a thematic role, we extract the matching object_property to the preposition.
# e.g I moved the bottle 'to' the table. The object_property takes the value "hasGoal"
#
# if the preposition is 'to' , by default we assume the indirect complement is an indirect object
# e.g. I gave a ball to Jido. The object_property takes the value "receivedBy"
# otherwise, the default processing is to create an object_property by concatenating is and the preposition
# e.g. I bought a ball for Jido. The object_property takes the value "isFor"
i_stmt_builder = NominalGroupStatementBuilder(ic.gn, self._current_speaker)
for ic_noun in ic.gn:
#Indirect object ID
if ic_noun.id:
ic_noun_id = ic_noun.id
else:
ic_noun_id = i_stmt_builder.set_nominal_group_id(ic_noun)
#Proposition role
icmpl_role = None
icmpl_qualification = None
# Case of no preposition
if not ic.prep:
icmpl_role = " receivedBy "
# Case of a preposition. Attempt to get from thematic roles
else:
icmpl_role = ResourcePool().thematic_roles.get_cmplt_role_for_preposition(verb, ic.prep[0], True)
# If no thematic role exist AND the verb is not a state
# verb, use the generic role 'involves' and try to qualify it properly.
# E.g: 'move the ball next to the table' ->
# action type Move, ..., action involves id1, id1 isNextTo table
if not icmpl_role:
try:
if verb not in ResourcePool().state:
icmpl_qualification = ResourcePool().preposition_rdf_object_property[ic.prep[0]][0]
else:
icmpl_role = " %s " % ResourcePool().preposition_rdf_object_property[ic.prep[0]][0]
except IndexError:
if ic.prep:
icmpl_qualification = "is" + ic.prep[0].capitalize()
#Creating statements
# Case of negation
if self._process_on_negative:
negative_ic_noun_id = generate_id(with_question_mark=False)
self._statements.append(sit_id + icmpl_role + negative_ic_noun_id)
self._statements.append(negative_ic_noun_id + ' owl:differentFrom ' + ic_noun_id)
# Case of affirmation
else:
if icmpl_qualification:
qualification_id = generate_id(with_question_mark=False)
self._statements += \
["%s involves %s" % (sit_id, qualification_id),
"%s %s %s" % (qualification_id, icmpl_qualification, ic_noun_id)]
else:
self._statements.append(sit_id + icmpl_role + ic_noun_id)
i_stmt_builder.process_nominal_group(ic_noun, ic_noun_id, None, False)
self._statements.extend(i_stmt_builder._statements)
self._unclarified_ids.extend(i_stmt_builder._unclarified_ids)
self.lear_more_concept.extend(i_stmt_builder.lear_more_concept)
def process_verb(self, verbal_group, subject_id, subject_quantifier, second_verb_sit_id):
for verb in verbal_group.vrb_main:
# Case 1: the state verb 'to be'/ to become"""
#Case 2: actions or stative verbs with a specified 'goal' or 'thematic' role:
# see '../../share/dialog/thematic_roles'
#Case 3: actions verbs with 'passive behaviour' like 'see'
#Case 4: special case for 'know'
#Case 5: other action or stative verbs
# Modal or phrasal verbs. E.g: can+do, look+for , ...
# verb = must+do
modal = ''
if '+' in verb:
# Case of Modals
[modal, verb] = verb.split('+')
if modal in ResourcePool().modal:
pass
#self._statements.append(sit_id + " rdf:type " + verb.capitalize())
#self._statements.append(subject_id+ " " + modal +"Performs " + sit_id)
#Case 1:
if verb in ResourcePool().state:
if isinstance(subject_id, basestring):
subjects_id = [subject_id]
else:
subjects_id = subject_id
agentslist = ResourcePool().ontology_server.listAgents()
if agentslist is None:
agentslist = [ResourcePool().default_model, self._current_speaker]
for subject_id in subjects_id:
if subject_id in agentslist:
sit_id = generate_id(with_question_mark=False)
self._statements.append(subject_id + " experiences " + sit_id)
else:
#TODO: Will keep only the last one is several ids
sit_id = subject_id
else:
# First, create a situation ID that represent the
# semantic situation carried by the verbal phrase
#Case : the verbal group that is being processed is the second verbs . i.e : it is held in the field sentence.sv.sv_sec
if second_verb_sit_id:
sit_id = second_verb_sit_id
# Case of question
elif self._process_on_question:
sit_id = '?event'
#case of negation : Creating a fake ID that is to find in the ontology for later removal
# Setting up the field process_statement_to_remove to True
elif self._process_on_negative:
sit_id = generate_id(with_question_mark=True)
self._unclarified_ids.append(sit_id)
self.process_statements_to_remove = True
# General case: we generate an ID
else:
sit_id = generate_id(with_question_mark=not self._process_on_resolved_sentence)
# Then, process the type of verb
#Case 2:
if verb in ResourcePool().goal_verbs:
self._statements.append(subject_id + " desires " + sit_id)
if verbal_group.sv_sec:
self.process_vrb_sec(verbal_group, subject_id, subject_quantifier, sit_id)
#Case 3: action verbs wit passive behaviour
elif verb.lower() in ResourcePool().action_verb_with_passive_behaviour.keys():
sit_id = subject_id
# Case 4: 'know'
elif verb.lower() == 'know':
pass
#Case 5: other verbs -> reification
else:
self._statements.append(sit_id + " rdf:type " + verb.capitalize())
self._statements.append(sit_id + " performedBy " + subject_id)
if not self._process_on_question and \
not self._process_on_negative \
and self._process_on_resolved_sentence:
# If I'm not processing a question, add a label
# to this action
self._statements.append(sit_id + " rdfs:label \"" + \
verb.capitalize() + " action #" + sit_id + "\"")
# Store the situation id
self.situation_id = sit_id
#Imperative specification, add the goal verb 'desire'
if self._process_on_imperative:
self._statements.append(self._current_speaker + " desires " + sit_id)
#Direct object
if verbal_group.d_obj:
self.process_direct_object(verbal_group.d_obj, verb, sit_id, subject_quantifier)
#Indirect Complement
if verbal_group.i_cmpl:
self.process_indirect_complement(verbal_group.i_cmpl, verb, sit_id)
# Adverbs modifiying the manner of an action verb
if verbal_group.vrb_adv:
self.process_action_verb_adverb(verbal_group.vrb_adv, verb, sit_id)
#verb tense
if verbal_group.vrb_tense:
self.process_verb_tense(verbal_group, verb, sit_id)
def clarify(self, description, ignoreFeatureL=None):
if not ignoreFeatureL: ignoreFeatureL = []
objL = self.get_all_objects_with_desc(description)
if len(objL) == 0:
logger.debug(colored_print('Nothing found!', "magenta"))
else:
logger.debug(
colored_print('Found these possible concepts ID: ', "magenta")
+ colored_print(str(objL), 'blue'))
if not self.oro: #No ontology server
return 'UNKNOWN_CONCEPT_' + generate_id(with_question_mark=False)
if not objL:
questions = SentenceFactory().create_i_dont_understand()
raise UnsufficientInputError({
'status': 'FAILURE',
'question': questions
})
#return "I don't understand"
else:
# Check if the speaker sees only some of the object.
# If he sees none of them, discriminate on the whole set.
# Else, discriminate only on visible objects.
agent = description[0][0]
logger.debug("Checking which of these objects are visible for " +
agent)
visible_objects = self.visible_subset(agent, objL)
if visible_objects:
objL = visible_objects
logger.debug(
colored_print('Only ', "magenta") +
colored_print(str(objL), 'blue') +
colored_print(" are visible by " + agent, "magenta"))
else:
logger.debug(
colored_print('None are visible by ' + agent, "magenta"))
if len(objL) == 1:
return objL[0]
if len(objL) == 2 and self.oro.check(
['%s owl:sameAs %s' % (objL[0], objL[1])]):
return objL[0]
agent, descriptor = self.get_descriptor(description,
ignoreFeatureL)
object = self.get_type_description(description)
if descriptor:
sentence_builder = SentenceFactory()
question = None
values = self.get_values_for_descriptor(
agent, descriptor, objL)
if not object: object = 'object'
if descriptor == 'hasColor' or descriptor == 'mainColorOfObject':
questions = sentence_builder.create_w_question_choice(
object, 'color', values)
elif descriptor == 'hasShape':
questions = sentence_builder.create_w_question_choice(
object, 'shape', values)
elif descriptor == 'hasSize':
questions = sentence_builder.create_w_question_choice(
object, 'size', values)
elif descriptor == 'isOn':
questions = sentence_builder.create_w_question_location(
object, 'on', values)
elif descriptor == 'isIn':
questions = sentence_builder.create_w_question_location(
object, 'in', values)
elif descriptor == 'isNextTo':
questions = sentence_builder.create_w_question_location(
object, 'next to', values)
elif descriptor == 'isAt':
questions = sentence_builder.create_w_question_location(
object, 'at', values)
elif descriptor == 'isLocated':
questions = sentence_builder.create_w_question_location_PT(
values, agent)
elif descriptor == 'rdf:type':
questions = sentence_builder.create_w_question_choice(
object, 'type', values)
else:
questions = sentence_builder.create_w_question_generic_descriptor(
object, descriptor, values)
raise UnsufficientInputError({
'status': 'SUCCESS',
'question': questions
})
#return questions
else:
questions = [
Sentence(IMPERATIVE, '', [], [
VerbalGroup(['give'], [], 'present simple', [
NominalGroup([], ['information'], [['more', []]],
[], [])
], [
IndirectComplement(
[], [NominalGroup([], ['me'], [], [], [])]),
IndirectComplement(
['about'],
[NominalGroup(['the'], [object], [], [], [])])
], [], [], VerbalGroup.affirmative, [])
])
]
raise UnsufficientInputError({
'status': 'SUCCESS',
'question': questions
})
def clarify(self, description, ignoreFeatureL=None):
if not ignoreFeatureL: ignoreFeatureL = []
objL = self.get_all_objects_with_desc(description)
if len(objL) == 0:
logger.debug(colored_print('Nothing found!', "magenta"))
else:
logger.debug(
colored_print('Found these possible concepts ID: ', "magenta") + colored_print(str(objL), 'blue'))
if not self.oro: #No ontology server
return 'UNKNOWN_CONCEPT_' + generate_id(with_question_mark=False)
if not objL:
questions = SentenceFactory().create_i_dont_understand()
raise UnsufficientInputError({'status': 'FAILURE', 'question': questions})
#return "I don't understand"
else:
# Check if the speaker sees only some of the object.
# If he sees none of them, discriminate on the whole set.
# Else, discriminate only on visible objects.
agent = description[0][0]
logger.debug("Checking which of these objects are visible for " + agent)
visible_objects = self.visible_subset(agent, objL)
if visible_objects:
objL = visible_objects
logger.debug(colored_print('Only ', "magenta") +
colored_print(str(objL), 'blue') +
colored_print(" are visible by " + agent, "magenta"))
else:
logger.debug(colored_print('None are visible by ' + agent, "magenta"))
if len(objL) == 1:
return objL[0]
if len(objL) == 2 and self.oro.check(['%s owl:sameAs %s' % (objL[0], objL[1])]):
return objL[0]
agent, descriptor = self.get_descriptor(description, ignoreFeatureL)
object = self.get_type_description(description)
if descriptor:
sentence_builder = SentenceFactory()
question = None
values = self.get_values_for_descriptor(agent, descriptor, objL)
if not object: object = 'object'
if descriptor == 'hasColor' or descriptor == 'mainColorOfObject':
questions = sentence_builder.create_w_question_choice(object, 'color', values)
elif descriptor == 'hasShape':
questions = sentence_builder.create_w_question_choice(object, 'shape', values)
elif descriptor == 'hasSize':
questions = sentence_builder.create_w_question_choice(object, 'size', values)
elif descriptor == 'isOn':
questions = sentence_builder.create_w_question_location(object, 'on', values)
elif descriptor == 'isIn':
questions = sentence_builder.create_w_question_location(object, 'in', values)
elif descriptor == 'isNextTo':
questions = sentence_builder.create_w_question_location(object, 'next to', values)
elif descriptor == 'isAt':
questions = sentence_builder.create_w_question_location(object, 'at', values)
elif descriptor == 'isLocated':
questions = sentence_builder.create_w_question_location_PT(values, agent)
elif descriptor == 'rdf:type':
questions = sentence_builder.create_w_question_choice(object, 'type', values)
else:
questions = sentence_builder.create_w_question_generic_descriptor(object, descriptor, values)
raise UnsufficientInputError({'status': 'SUCCESS', 'question': questions})
#return questions
else:
questions = [Sentence(IMPERATIVE, '', [],
[Verbal_Group(['give'], [], 'present simple',
[Nominal_Group([], ['information'], [['more', []]], [], [])],
[Indirect_Complement([], [Nominal_Group([], ['me'], [], [], [])]),
Indirect_Complement(['about'], [
Nominal_Group(['the'], [object], [], [], [])])],
[], [], Verbal_Group.affirmative, [])])]
raise UnsufficientInputError({'status': 'SUCCESS', 'question': questions})
