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from collections import defaultdict
from modelscope.utils.constant import Tasks
from .pipeline_tool import ModelscopePipelineTool
class TextNerTool(ModelscopePipelineTool):
default_model = 'damo/nlp_raner_named-entity-recognition_chinese-base-news'
description = '命名实体识别服务,针对需要识别的中文文本,找出其中的实体,返回json格式结果'
name = 'modelscope_text-ner'
parameters: list = [{
'name': 'input',
'description': '用户输入的文本',
'required': True
}]
task = Tasks.named_entity_recognition
def _parse_output(self, origin_result, *args, **kwargs):
final_result = defaultdict(list)
for e in origin_result['output']:
final_result[e['type']].append(e['span'])
return {'result': dict(final_result)}