论文标题
BERN2：一种先进的神经生物医学命名实体识别和标准化工具
BERN2: an advanced neural biomedical named entity recognition and normalization tool
论文作者
论文摘要
在生物医学自然语言处理中，指定的实体识别（NER）和指定的实体归一化（NEN）是能够从不断增长的生物医学文献中自动提取生物医学实体（例如疾病和药物）的关键任务。在本文中，我们介绍了BERN2（高级生物医学实体识别和归一化），该工具通过采用多任务NER模型和基于神经网络的NEN模型来改善以前的基于神经网络的NER工具，以实现更快，更准确的推断。我们希望我们的工具可以帮助注释大规模的生物医学文本，以完成各种任务，例如生物医学知识图构造。
In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e.g. diseases and drugs) from the ever-growing biomedical literature. In this article, we present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by employing a multi-task NER model and neural network-based NEN models to achieve much faster and more accurate inference. We hope that our tool can help annotate large-scale biomedical texts for various tasks such as biomedical knowledge graph construction.
