BriefGPT.xyz
Jul, 2021
上下文感知对抗训练用于解决命名实体识别中的名称规律偏见
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition
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Abbas Ghaddar, Philippe Langlais, Ahmad Rashid, Mehdi Rezagholizadeh
TL;DR
本研究检测了命名实体识别（NER）模型在预测不确定实体类型时使用上下文信息的能力，设计了NRB测试集来诊断NER模型的名称规律偏差，并提出了一种新的模型无关训练方法来减轻这种偏差，该方法对改善NER模型性能有显著作用。
Abstract
In this work, we examine the ability of
ner models
to use
contextual information
when predicting the type of an ambiguous entity. We introduce NRB, a new testbed carefully designed to diagnose
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