Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

Crime continues to remain a severe threat to all communities and nations across the globe
alongside the sophistication in technology and processes that are being exploited to enable …

This survey covers fifteen years of research in the Named Entity Recognition and
Classification (NERC) field, from 1991 to 2006. We report observations about languages …

Named-entity recognition (NER) aims at identifying entities of interest in a text. Artificial
neural networks (ANNs) have recently been shown to outperform existing NER systems …

This paper proposes a Hidden Markov Model (HMM) and an HMM-based chunk tagger, from
which a named entity (NE) recognition (NER) system is built to recognize and classify …

This thesis describes a novel statistical named-entity (ie “proper name”) recognition system
known as “MENE”(Maximum Entropy Named Entity). Named entity (NE) recognition is a form …

摘要命名实体识别一直以来都是信息抽取, 自然语言处理等领域中重要的研究任务,
随着机器学习技术的新发展, 数字人文研究的兴起, 事件知识和实体知识变得越发重要 …

Identification of named entities from legal texts is an essential building block for developing
other legal Artificial Intelligence applications. Named Entities in legal texts are slightly …

Recognizing and extracting exact name entities, like Persons, Locations and Organizations
are very useful to mining information from text. Learning to extract names in natural …

This paper describes a novel statistical namedentity (ie" proper name") recognition system
built around a maximum entity framework. By working v, ithin the framework of maximum …