def parse_events(text, stem_pos=True, corelex=True, pass_coreference=False):
pos, tree, deps, corefs = stanford_nlp.get_parses(text, coreferences=True)
clusters = defaultdict(list)
for coref in corefs:
clusters[coref['corefClusterID']].append(coref)
chains = list()
for id, chain in clusters.iteritems():
chains.append(chain)
for chain in chains:
l = list()
for coreference in chain:
mention = coreference['mentionSpan']
sentence = coreference['sentNum']
events = match2(mention=mention,
dependencies=deps[sentence - 1],
coreference=coreference)
if [] != events:
l.append(events)
if [] != l:
print l
##over a list of dependencies
nodes = []
verbs = []
for sent in sents:
negs = get_negs(sent)
nodes.extend(negs[1])
verbs.append(negs[0])
nodes = [node for node in nodes if node['relation'] != "neg"]
#the verbs and the nodes need to be treated differently, nodes are nodes, verbs are strings
return (verbs, nodes)
if __name__ == '__main__':
tag = "?"
sentence = '"Life threatening condition that is always physically harmful"? What a giant load of steamy BS.'
print sentence
pos,meta,dependency = stanford_nlp.get_parses(sentence)
nodes = question_nodes(dependency)
print sisters.label(nodes, tag)
tag = "quote"
sentence = '"Life threatening condition that is always physically harmful"? What a giant load of steamy BS.'
print sentence
pos,meta,dependency = stanford_nlp.get_parses(sentence)
words = quote_nodes(pos, dependency)
print sisters.label(words, tag)
tag = "quote"
sentence = "John said 'I like cookies.'"
print sentence
pos,meta,dependency = stanford_nlp.get_parses(sentence)
