def create_semantic_structures(frame_semantic_list):
"""Take in the list of VerbNet frames and generate the semantic
representation structures from them."""
semantic_representation_list = []
conditional = False
# Frame semantic list is a list of conjunction strings and tuples, where the
# first element of the tuple is the frame semantics, the second element is
# the original tree branch it came from, and the third is a list of tags.
for frame in frame_semantic_list:
# Check that this is a VerbNet frame and not a conjunction
try:
frame_items = frame[0].items()
except:
if 'if' in str(frame):
conditional = True
frame_items = None
semantic_representation_list.append(frame)
continue
verb = frame[3].split('-')[0]
location_predicates = defaultdict(list)
location_resolved = False
entity_class_dict = {}
for key, value in frame_items:
entity_class_dict[key] = extract_entity_class(value, key)
wh_question_type = frames.get_wh_question_type(str(frame[1]))
# If it's a WH-question, find the type of question it is and add the object
if wh_question_type is not None and 'Theme' in entity_class_dict:
semantic_representation_list.append(\
WhQuery(entity_class_dict['Theme'], wh_question_type))
# If it's a yes-no question, add the theme of the question
elif frames.is_yn_question(str(frame[1])):
if 'Theme' in entity_class_dict and 'Location' in entity_class_dict:
entity_class_dict['Theme'].predicates = \
dict(entity_class_dict['Theme'].predicates.items() +
entity_class_dict['Location'].predicates.items() )
semantic_representation_list.append(\
YNQuery(entity_class_dict['Theme']))
# If there is a specific location involved, it's a command (this may need to be changed)
elif location_resolved is True:
semantic_representation_list.append(
Command(str(location_predicates['Location'][0]),'go'))
# If there was a conditional statement, this command ends it
conditional = False
# If it's a conditional statement, the first statement is an event
elif conditional is True and 'Theme' in entity_class_dict:
semantic_representation_list.append(Event(entity_class_dict['Theme'], verb))
# It's a regular command
elif verb is not None and verb != 'be':
command_predicate_dict = {}
for key, value in entity_class_dict.items():
# Only add semantic roles, not prepositions and verbs
if key == string.capitalize(key):
command_predicate_dict[key] = value.predicates[key]
for key, value in entity_class_dict.items():
if key == 'Theme' or key == 'Agent' or key == 'Patient':
semantic_representation_list.append(Command(
EntityClass(
value.quantifier,
command_predicate_dict),
verb))
break
# It's an assertion
else:
semantic_representation_list.append(\
Assertion(entity_class_dict['Theme'], entity_class_dict['Location'].predicates,\
('ex' in frame[2])))
return semantic_representation_list
def create_semantic_structures(frame_semantic_list):
"""Take in the list of VerbNet frames and generate the semantic
representation structures from them."""
semantic_representation_list = []
conditional = False
# Frame semantic list is a list of conjunction strings and tuples, where the
# first element of the tuple is the frame semantics, the second element is
# the original tree branch it came from, the third is a list of tags, and
# the fourth is the sense.
for frame in frame_semantic_list:
# Check that this is a VerbNet frame and not a conjunction
try:
frame_items = frame[0].items()
except AttributeError:
if 'if' in str(frame):
conditional = True
frame_items = None
#semantic_representation_list.append(frame)
continue
sense = frame[3].split('-')[0]
# Get the action associated with the sense
# If such a mapping does not exist, use the original verb
action = ACTION_ALIASES.get(sense, frame[4])
item_to_entity = {key:extract_entity(value, key) for key, value in frame_items}
wh_question_type = frames.get_wh_question_type(str(frame[1]))
# If it's a WH-question, find the type of question it is and add the object
if wh_question_type is not None:
if wh_question_type == 'Status':
semantic_representation_list.append(StatusQuery())
elif 'Theme' in item_to_entity:
if wh_question_type == 'Location':
semantic_representation_list.append(LocationQuery(item_to_entity['Theme']))
elif wh_question_type in ('People', 'Entity'):
semantic_representation_list.append(EntityQuery(item_to_entity['Location']))
# If it's a yes-no question, add the theme and location of the question
elif frames.is_yn_question(str(frame[1])):
if 'Theme' in item_to_entity and 'Location' in item_to_entity:
semantic_representation_list.append(YNQuery(item_to_entity['Theme'], item_to_entity['Location']))
# If it's a conditional statement, the first statement is an event or an assertion
elif conditional:
if 'Stimulus' in item_to_entity:
condition = Event(item_to_entity['Stimulus'], action)
else:
condition = Assertion(item_to_entity.get('Theme', None),\
item_to_entity.get('Location', None),\
'ex' in frame[2])
if len(semantic_representation_list) > 0 and isinstance(semantic_representation_list[-1], Command):
semantic_representation_list[-1].condition = condition
else:
# Dangling condition (shouldn't happen)
semantic_representation_list.append(condition)
# It's a regular command
elif action is not None and action not in ('is', 'are', 'be'):
theme = item_to_entity.get('Theme', None)
agent = item_to_entity.get('Agent', None)
patient = item_to_entity.get('Patient', None)
if patient is None:
patient = item_to_entity.get('Recipient', None)
location = item_to_entity.get('Location', None)
source = item_to_entity.get('Source', None)
destination = item_to_entity.get('Destination', None)
current_command = Command(agent, theme, patient, location, source, destination, action, negation=frame[5])
semantic_representation_list.append(current_command)
# It's an assertion
else:
semantic_representation_list.append(Assertion(item_to_entity.get('Theme', None),
item_to_entity.get('Location', None),
'ex' in frame[2]))
if EXTRACT_DEBUG:
print 'Semantic representation list:'
print semantic_representation_list
return semantic_representation_list