论文标题
Protagonisttagger-一种在各种语言和领域的文本中人物实体链接的工具
ProtagonistTagger -- a Tool for Entity Linkage of Persons in Texts from Various Languages and Domains
论文作者
论文摘要
命名实体识别（NER）和歧义（NED）可以在文本中的公认命名实体中添加语义上下文。无论域如何，文本中的命名实体链接都提供了在非结构化文本中提到的实体与现实世界对象的各个实例之间的链接。在这张海报中，我们为人物和ned提供了一种工具 - promagonisttagger。该工具已在经典英语小说和波兰互联网新闻中提取的文本中进行了测试。该工具的性能（精度和召回）在78％甚至88％之间波动。
Named entities recognition (NER) and disambiguation (NED) can add semantic context to the recognized named entities in texts. Named entity linkage in texts, regardless of a domain, provides links between the entities mentioned in unstructured texts and individual instances of real-world objects. In this poster, we present a tool - protagonistTagger - for person NER and NED in texts. The tool was tested on texts extracted from classic English novels and Polish Internet news. The tool's performance (both precision and recall) fluctuates between 78% and even 88%.
