def get_evaluation_document(cluster_info, gold_info, max_cluster_num):
predict = []
for i in range(max_cluster_num):
predict.append([])
for mention_num in range(len(cluster_info)):
cluster_num = cluster_info[mention_num]
predict[cluster_num].append(mention_num)
ev_document = evaluation.EvaluationDocument(gold_info, predict)
return ev_document
def get_evaluation_document(cluster_info, gold_info, doc_ids, max_cluster_num):
predict = []
predict_dict = {}
for mention_num in range(len(cluster_info)):
cluster_num = cluster_info[mention_num]
predict_dict.setdefault(cluster_num, [])
predict_dict[cluster_num].append(doc_ids[mention_num])
#predict[cluster_num].append(mention_num)
for k in sorted(predict_dict.keys()):
predict.append(predict_dict[k])
ev_document = evaluation.EvaluationDocument(gold_info, predict)
return ev_document
def get_evaluation_document(cluster_info, gold_info, max_cluster_num):
predict = []
for i in range(max_cluster_num):
predict.append([])
for mention_num in range(len(cluster_info)):
cluster_num = cluster_info[mention_num]
predict[cluster_num].append(mention_num)
'''
print "a"
for s in predict:
if len(s) > 1:
print s
print
print gold_info
'''
ev_document = evaluation.EvaluationDocument(gold_info, predict)
return ev_document