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Named Entity Recognition by Conditional Random Fields from Turkish informal texts

机译:来自土耳其非正式文本的条件随机字段命名的实体识别

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Named Entity Recognition (NER) being one of the areas of Natural Language processing can be domain dependent or independent for formal and informal texts aims to extract information about name entity such as person, location, organization, dates, formula and money. Rule Based methods and machine learning methods can be implemented in the system. In this study, Conditional Random Fields has been used to extract name entities which are person, location and organization names from informal texts.
机译:命名实体识别(NER)是自然语言处理的领域之一,可以依赖于域,也可以独立于正式和非正式文本,目的是提取有关名称实体的信息,例如人,位置,组织,日期,公式和金钱。可以在系统中实现基于规则的方法和机器学习方法。在这项研究中,条件随机字段已被用于从非正式文本中提取名称实体,即人物,位置和组织名称。

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