This paper describes a new, freely available, highly multilingual named
entity resource for person and organisation names that has been compiled over
seven years of large-scale multilingual news analysis combined with Wikipedia
mining, resulting in 205,000 per-son and organisation names plus about the same
number of spelling variants written in over 20 different scripts and in many
more languages. This resource, produced as part of the Europe Media Monitor
activity (EMM, this http URL), can be used for a number
of purposes. These include improving name search in databases or on the
internet, seeding machine learning systems to learn named entity recognition
rules, improve machine translation results, and more. We describe here how this
resource was created; we give statistics on its current size; we address the
issue of morphological inflection; and we give details regarding its
functionality. Updates to this resource will be made available daily.

本研究描述了一种新的，免费提供的、高度多语种的名义实体资源，包含了经过七年大规模多语言新闻分析和维基百科挖掘编制的 20 多种语言、20 万个人名和组织名及同样数量的拼写变体。该资源可以用于改进数据库或互联网上的名称搜索，为机器学习系统提供学习命名实体识别规则，改善机器翻译等。我们在此描述了该资源的创建方式、当前规模的统计数据、形态学屈折问题的解决方案以及其功能的详细信息。该资源的更新将每日提供。