Combining contextualized word representation and sub-document level analysis through Bi-LSTM+ CRF architecture for clinical de-identification
Clinical de-identification aims to identify Protected Health Information in clinical data,
enabling data sharing and publication. First automatic de-identification systems were based …
enabling data sharing and publication. First automatic de-identification systems were based …
[PDF][PDF] 基于深度学习的命名实体识别综述
邓依依， 邬昌兴， 魏永丰， 万仲保， 黄兆华 - 中文信息学报, 2021 - jcip.cipsc.org.cn
命名实体识别是自然语言处理的基础任务之一, 目的是从非结构化的文本中识别出所需的实体及
类型, 其识别的结果可用于实体关系抽取, 知识图谱构建等众多实际应用. 近些年 …
类型, 其识别的结果可用于实体关系抽取, 知识图谱构建等众多实际应用. 近些年 …
Uamner: uncertainty-aware multimodal named entity recognition in social media posts
Abstract Named Entity Recognition (NER) on social media is a challenging task, as social
media posts are usually short and noisy. Recently, some work explores different ways to …
media posts are usually short and noisy. Recently, some work explores different ways to …
Explicitly capturing relations between entity mentions via graph neural networks for domain-specific named entity recognition
Named entity recognition (NER) is well studied for the general domain, and recent systems
have achieved human-level performance for identifying common entity types. However, the …
have achieved human-level performance for identifying common entity types. However, the …
Exploiting global contextual information for document-level named entity recognition
Named entity recognition (NER, also known as entity chunking/extraction) is a fundamental
sub-task of information extraction, which aims at identifying named entities from an …
sub-task of information extraction, which aims at identifying named entities from an …
Consistency enhancement of model prediction on document-level named entity recognition
Biomedical named entity recognition (NER) plays a crucial role in extracting information from
documents in biomedical applications. However, many of these applications require NER …
documents in biomedical applications. However, many of these applications require NER …
Improving biomedical named entity recognition by dynamic caching inter-sentence information
Abstract Motivation Biomedical Named Entity Recognition (BioNER) aims to identify
biomedical domain-specific entities (eg gene, chemical and disease) from unstructured …
biomedical domain-specific entities (eg gene, chemical and disease) from unstructured …
Enhancing label consistency on document-level named entity recognition
Named entity recognition (NER) is a fundamental part of extracting information from
documents in biomedical applications. A notable advantage of NER is its consistency in …
documents in biomedical applications. A notable advantage of NER is its consistency in …
Semi-supervised named entity recognition in multi-level contexts
Named entity recognition is a critical task in the natural language processing field. Most
existing methods for this task can only exploit contextual information within a sentence …
existing methods for this task can only exploit contextual information within a sentence …
Span Graph Transformer for Document-Level Named Entity Recognition
Named Entity Recognition (NER), which aims to identify the span and category of entities
within text, is a fundamental task in natural language processing. Recent NER approaches …
within text, is a fundamental task in natural language processing. Recent NER approaches …