Results of the WNUT2017 Shared Task on Novel and Emerging Entity Recognition

NUT@EMNLP Pub Date : 2017-09-01 DOI:10.18653/v1/W17-4418
Leon Derczynski, Eric Nichols, M. Erp, Nut Limsopatham
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引用次数: 294

Abstract

This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. Named entities form the basis of many modern approaches to other tasks (like event clustering and summarization), but recall on them is a real problem in noisy text - even among annotators. This drop tends to be due to novel entities and surface forms. Take for example the tweet “so.. kktny in 30 mins?!” – even human experts find the entity ‘kktny’ hard to detect and resolve. The goal of this task is to provide a definition of emerging and of rare entities, and based on that, also datasets for detecting these entities. The task as described in this paper evaluated the ability of participating entries to detect and classify novel and emerging named entities in noisy text.
WNUT2017新实体和新兴实体识别共享任务结果
这项共同任务的重点是在新兴讨论的背景下识别不寻常的、以前看不见的实体。命名实体构成了许多处理其他任务(如事件聚类和摘要)的现代方法的基础,但是在嘈杂的文本中对它们的调用是一个真正的问题——即使在注释器中也是如此。这种下降往往是由于新的实体和表面形式。举个例子,“所以……”Kktny在30分钟内?——即使是人类专家也发现这种实体“kktny”很难检测和解决。本任务的目标是提供新兴实体和稀有实体的定义,并在此基础上提供用于检测这些实体的数据集。本文描述的任务评估了参与条目在嘈杂文本中检测和分类新颖和新兴命名实体的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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