ALANNO: An Active Learning Annotation System for Mortals
November 11, 2022 Β· Declared Dead Β· π Conference of the European Chapter of the Association for Computational Linguistics
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Authors
Josip JukiΔ, Fran JeleniΔ, Miroslav BiΔaniΔ, Jan Ε najder
arXiv ID
2211.06224
Category
cs.LG: Machine Learning
Citations
4
Venue
Conference of the European Chapter of the Association for Computational Linguistics
Last Checked
3 months ago
Abstract
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.
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