Named Entity Recognition Ner On Ontonotes V5

Métriques

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	F1	Paper Title	Repository
Syn-LSTM + BERT (wo doc-context)	90.85	Better Feature Integration for Named Entity Recognition
DGLSTM-CRF + ELMo	89.88	Dependency-Guided LSTM-CRF for Named Entity Recognition
BiLSTM-LAN	88.16	Hierarchically-Refined Label Attention Network for Sequence Labeling
Bi-LSTM-CRF + Lexical Features	87.95	Robust Lexical Features for Improved Neural Network Named-Entity Recognition
PL-Marker	91.9	Packed Levitated Marker for Entity and Relation Extraction
Syn-LSTM (wo doc-context)	89.04	Better Feature Integration for Named Entity Recognition
BERT-MRC	91.11	A Unified MRC Framework for Named Entity Recognition
Hierarchical	87.98	Hierarchical Contextualized Representation for Named Entity Recognition
BiLSTM-CRF	86.99	Fast and Accurate Entity Recognition with Iterated Dilated Convolutions
DGLSTM-CRF (L=2)	88.52	Dependency-Guided LSTM-CRF for Named Entity Recognition
Joint Model	84.04	A Joint Model for Entity Analysis: Coreference, Typing, and Linking	-
Biaffine-NER	91.3	Named Entity Recognition as Dependency Parsing
CVT + Multi-Task + Large	88.81	Semi-Supervised Sequence Modeling with Cross-View Training
HSCRF + softdict	89.94	Towards Improving Neural Named Entity Recognition with Gazetteers
Att-BiLSTM-CNN	88.4	Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER
BARTNER	90.38	A Unified Generative Framework for Various NER Subtasks
NuNER	89.1	NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data
W2NER	90.50	Unified Named Entity Recognition as Word-Word Relation Classification
AESINER	90.32	Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
GRN	87.67	GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition

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