Hierarchical Region Learning for Nested Named Entity Recognition.doi:10.18653/V1/2020.FINDINGS-EMNLP.430Xinwei LongShuzi NiuYucheng LiAssociation for Computational LinguisticsEmpirical Methods in Natural Language Processing
Named Entity Recognition (NER) aims to extract structured entity information from unstructured textual data by identifying entity boundaries and categories. Chinese NER is more challenging than that of English due to the complex structure and ambiguous word boundaries, as well as nested and discontinuous...
题目Nested Named Entity Recognition via Second-best Sequence Learning and Decoding 通过次优序列学习和解码嵌套命名实体识别 摘要 在训练神经模型上,设计了一个目标函数去处理嵌套实体的标签序列作为在双新实体跨度的次优路径; 在解码预测上,使用从外部到内部的迭代提取实体的方式; 效果为目前领先。 问题背景 这个句...
The optimization of the HPC-XGB hyperparameters was performed by implementing a grid-search and optimizing the macro-recall score in a nested LOGPO. Hence, each split of the outer loop was trained with the optimal hyperparameters tuned in the inner loop. Although this procedure is ...
Collins, Michael, “Ranking Algorithms for Named-Entity Extraction: Boosting and the Voted Perceptron,” Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, Jul. 2002, pp. 489-496. Crescenzi, Valter, Giansalvatore Mecca and Paolo Merialdo, “RoadRunn...