def get_semantics_from_parse_tree(parse_tree_string):
"""Take a string representing the parse tree as input, and print the
semantic parse. The result list consists of a list of tuples, with each
tuple containing the VerbNet frame and its associated tree."""
parse_tree = Tree.parse(parse_tree_string)
# Split clauses to handle them separately
split_clause_dict = frames.split_clauses(parse_tree)
# Activize clauses
for key, (clause, conjunction) in split_clause_dict.items():
activized_clause = frames.activize_clause(clause)
split_clause_dict[key] = (activized_clause, conjunction)
result_list = []
for (clause, conjunction) in split_clause_dict.values():
# Split conjunctions and duplicate arguments if necessary
split_tree_dict = frames.split_conjunctions(clause)
if conjunction != '':
result_list.append(conjunction)
for (split_tree, conjunction) in split_tree_dict.values():
if conjunction != '':
result_list.append(conjunction)
for tree in split_tree:
tag_list = []
# Store whether there was an existential there
if frames.is_existential(str(tree)):
tag_list.append('ex')
# Transformational grammar stuff
tree = frames.existential_there_insertion(tree)
tree = frames.invert_clause(tree)
tree = frames.wh_movement(tree)
# Regex for finding verbs
verb_finder = re.compile(r'(?<=VB[ DGNPZ]) *\w*(?=\))')
# Get the lemma of the verb for searching verbnet
verbs = (word.strip().lower() for word in
verb_finder.findall(str(tree)))
# Create VFOs for each verb, then match them to the parse tree
for verb in verbs:
lemmatized_verb = morphy(verb,'v')
vfo_list = frames.create_VerbFrameObjects(lemmatized_verb)
match_list = []
for vfo in vfo_list:
match = vfo.match_parse(tree)
if match:
match_list.append((match, vfo.classid))
(best_match, sense) = frames.pick_best_match(match_list)
if not best_match is None:
result_list.append((best_match, tree, tag_list, sense))
return result_list
def extract_frames_from_parse(parse_tree_string):
"""Take a string representing the parse tree as input, and print the
semantic parse. The result list consists of a list of tuples, with each
tuple containing the VerbNet frame and its associated tree."""
result_list = []
# In case we're handed an bad string, bail somewhat gracefully
try:
parse_tree = Tree.parse(parse_tree_string)
except ValueError:
print "Warning: semantics could not parse tree", repr(parse_tree_string)
return result_list
# Split clauses to handle them separately
split_clause_dict = frames.split_clauses(parse_tree)
# Activize clauses
for key, (clause, conjunction) in split_clause_dict.items():
activized_clause = frames.activize_clause(clause)
split_clause_dict[key] = (activized_clause, conjunction)
for (clause, conjunction) in split_clause_dict.values():
# Split conjunctions and duplicate arguments if necessary
split_tree_dict = frames.split_conjunctions(clause)
if conjunction != '':
result_list.append(conjunction)
for (split_tree, conjunction) in split_tree_dict.values():
if conjunction != '':
result_list.append(conjunction)
for tree in split_tree:
tag_list = []
# Store whether there was an existential there
if frames.is_existential(str(tree)):
tag_list.append('ex')
# Transformational grammar stuff
tree = frames.existential_there_insertion(tree)
tree = frames.invert_clause(tree)
tree = frames.wh_movement(tree)
if EXTRACT_DEBUG:
print 'Transformed tree:'
print str(tree)
verbs = frames.find_verbs(tree)
# Create VFOs for each verb, then match them to the parse tree
for verb, negation in verbs:
lemmatized_verb = morphy(verb, 'v')
vfo_list = frames.create_VerbFrameObjects(lemmatized_verb)
match_list = []
if EXTRACT_DEBUG:
print 'VFO list for %s:' % verb
print '\n'.join(str(vfo.frame_list) for vfo in vfo_list)
for vfo in vfo_list:
match = vfo.match_parse(tree)
if match:
if EXTRACT_DEBUG:
print 'Matched:'
print '\t', str(vfo.frame_list)
print 'with'
print '\t', str(tree)
match_list.append((match, vfo.classid))
if EXTRACT_DEBUG:
print 'Match list:'
for m in match_list:
print 'Sense:', m[1]
for a, b in m[0].items():
print a, str(b)
print '\n\n'
(best_match, sense) = frames.pick_best_match(match_list)
if EXTRACT_DEBUG:
print 'Chose: '
if best_match:
for a, b in best_match.items():
print a, str(b)
else:
print str(None)
print '\n\n'
if not best_match is None:
result_list.append((best_match, tree, tag_list, sense, verb, negation))
return result_list