Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

We study the task of recognizing named datasets in scientific articles as a Named Entity
Recognition (NER) problem. Noticing that available annotated datasets were not adequate …

Evidence plays a crucial role in any biomedical research narrative, providing justification for
some claims and refutation for others. We seek to build models of scientific argument using …

Recent advances in large pre-trained language models have demonstrated strong results in
generating natural languages and significantly improved performances for many natural …

Biomedical Named Entity Recognition (BioNER) aims at identifying biomedical entities such
as genes, proteins, diseases, and chemical compounds in the given textual data. However …

Understanding how events are semantically related to each other is the essence of reading
comprehension. Recent event-centric reading comprehension datasets focus mostly on …

Abstract Safety Data Sheets (SDS) provide essential safety and health information for
various substances and products. They are widely used in industries that require …

In the modern economic landscape, integrating financial services with Financial Technology
(FinTech) has become essential, particularly in stock trend analysis. This study addresses …

摘要针对多源异构的网络安全数据的离散分布问题, 总结了知识图谱构建需要的网络空间战技术
, 攻击模式, 漏洞及网络设备等基础数据, 提炼了数据之间的关联关系. 在此基础上 …