本文对自然语言基础技术之命名实体识别进行了相对全面的介绍,包括定义、发展历史、常见方法、以及相关数据集,最后推荐一大波 Python 实战利器,并且包括工具的用法。01定义先来看看维基百科上的定义:Named-entity recognition (NER) (also known as entity identification, entity chunking and entity extraction) is a subtask of information extraction that seeks to locate and classify named entity mentions in unstructured text into pre-defined categories such as the person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.命名实体识别(Named Entity Recognition,简称NER),又称作“专名识别”,是指识别文本中具有特定意义的实体,主要包括人名、地名、机构名、专有名词等。简单的讲,就是识别
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