Entity Typing On Open Entity 1

Results

Performance results of various models on this benchmark

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

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