基于混合搜索的增强命名实体注释工具

Krati Saxena, Sagar Sunkle, V. Kulkarni
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引用次数: 0

摘要

识别命名实体是从文本中提取信息的关键步骤。训练NER模型通常需要带注释的数据。人类注释者花费大量时间和精力注释大型数据集。本文介绍了一种新的基于混合搜索的增强型标注工具。注释工具提供了一个易于使用的GUI和几种搜索模式来加速注释练习。用户可以查找相似的文本和术语,并在结果中注释信息。我们将演示我们的工具的实用性,并将我们的工具与其他工具进行比较。我们展示了它提供了比典型注释器更快的注释,并且与最先进的工具具有相当的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid Search based Enhanced Named Entity Annotation Tool
Identifying named entities is a crucial step in extracting information from text. Training NER models usually require annotated data. Human annotators spend a lot of time and effort annotating large datasets. In this paper, we introduce a novel hybrid search-based enhanced annotation tool. The annotation tool provides an easy-to-use GUI and several search modes to accelerate the annotation exercise. Users can look for similar text and terms and annotate the information in the results. We demonstrate the utility of our tool and evaluate our tool in comparison with other tools. We show that it provides faster annotation than typical annotators and comparable performance with state-of-the-art tools.
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