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Named Entity Recognition Ner On Conll 2003

Metrics

F1

Results

Performance results of various models on this benchmark

Paper TitleRepository
ACE + document-context94.6Automated Concatenation of Embeddings for Structured Prediction
LUKE 483M94.3LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
Co-regularized LUKE94.22Learning from Noisy Labels for Entity-Centric Information Extraction
LUKE + SubRegWeigh (K-means)94.2SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization
ASP+T5-3B94.1Autoregressive Structured Prediction with Language Models
FLERT XLM-R94.09FLERT: Document-Level Features for Named Entity Recognition
PL-Marker94.0Packed Levitated Marker for Entity and Relation Extraction
CL-KL93.85Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
XLNet-GCN93.82Named entity recognition architecture combining contextual and global features
RoBERTa + SubRegWeigh (K-means)93.81SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization
ASP+flan-T5-large93.8Autoregressive Structured Prediction with Language Models
InferNER93.76InferNER: an attentive model leveraging the sentence-level information for Named Entity Recognition in Microblogs-
Cross-sentence context (First)93.74Exploring Cross-sentence Contexts for Named Entity Recognition with BERT
XLM-RoBERTa-large union93.69Transformer-based Named Entity Recognition with Combined Data Representation-
Baseline + BS93.65Boundary Smoothing for Named Entity Recognition
ACE93.64Automated Concatenation of Embeddings for Structured Prediction
BERT-CRF93.6Focusing on Potential Named Entities During Active Label Acquisition
CNN Large + fine-tune93.5Cloze-driven Pretraining of Self-attention Networks-
Biaffine-NER93.5Named Entity Recognition as Dependency Parsing
I-DARTS + Flair93.47Improved Differentiable Architecture Search for Language Modeling and Named Entity Recognition-
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Named Entity Recognition Ner On Conll 2003 | SOTA | HyperAI