论文标题
Alanno：凡人的主动学习注释系统
ALANNO: An Active Learning Annotation System for Mortals
论文作者
论文摘要
监督的机器学习已成为当今数据驱动社会的基石，增加了对数据的需求。但是，获取标签的过程通常昂贵且乏味。一种可能的补救措施是使用主动学习（AL） - 一种特殊的机器学习算法系列，旨在降低标签成本。尽管AL在实践中取得了成功，但许多实际的挑战都阻碍了其有效性，并且在现有的AL注释工具中经常被忽略。为了应对这些挑战，我们开发了Alanno，这是一个开源注释系统，用于配备功能，可在现实世界中有效的NLP任务。 Alanno促进了多通道设置中的注释管理，并支持各种AL方法和基础模型，这些模型易于配置和扩展。
Supervised machine learning has become the cornerstone of today's data-driven society, increasing the need for labeled data. However, the process of acquiring labels is often expensive and tedious. One possible remedy is to use active learning (AL) -- a special family of machine learning algorithms designed to reduce labeling costs. Although AL has been successful in practice, a number of practical challenges hinder its effectiveness and are often overlooked in existing AL annotation tools. To address these challenges, we developed ALANNO, an open-source annotation system for NLP tasks equipped with features to make AL effective in real-world annotation projects. ALANNO facilitates annotation management in a multi-annotator setup and supports a variety of AL methods and underlying models, which are easily configurable and extensible.
