Entity Typing On Open Entity 1

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	F1	Paper Title	Repository
MLMET	49.1	Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
LRN	45.4	Fine-grained Entity Typing via Label Reasoning	-
LDET	40.1	Learning to Denoise Distantly-Labeled Data for Entity Typing
RoBERTa-Large + NPCRF (replicated by Adaseq)	47.3	Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field
Prompt + NPCRF (replicated by Adaseq)	50.1	Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field
LabelGCN	36.9	Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing
UFET-biLSTM	31.3	Ultra-Fine Entity Typing
Box4Type	44.8	Modeling Fine-Grained Entity Types with Box Embeddings
UniST-Large	49.9	Unified Semantic Typing with Meaningful Label Inference
MCCE-B (replicated by Adaseq)	52.1	Recall, Expand and Multi-Candidate Cross-Encode: Fast and Accurate Ultra-Fine Entity Typing
MLMET	78.2	LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
RoBERTa-Large (replicated by Adaseq)	43.8	Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field
Prompt Learning (replicated by Adaseq)）	49.3	Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field

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