Entity Linking On Wic Tsv

Task 1 Accuracy: all

Task 1 Accuracy: domain specific

Task 1 Accuracy: general purpose

Task 2 Accuracy: all

Task 2 Accuracy: domain specific

Task 2 Accuracy: general purpose

Task 3 Accuracy: all

Task 3 Accuracy: domain specific

Task 3 Accuracy: general purpose

Results

Performance results of various models on this benchmark

Model Name	Task 1 Accuracy: all	Task 1 Accuracy: domain specific	Task 1 Accuracy: general purpose	Task 2 Accuracy: all	Task 2 Accuracy: domain specific	Task 2 Accuracy: general purpose	Task 3 Accuracy: all	Task 3 Accuracy: domain specific	Task 3 Accuracy: general purpose	Paper Title	Repository
Bert-base	75.3	77.9	73.3	71.7	74.7	68.6	76.6	80.4	73.5	WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context
GlossBert-ws	75.9	76.7	75.2	-	-	-	-	-	-	GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge
Unsupervised Bert	54.4	60.6	49.2	62.8	69.1	57.6	60.5	67.9	54.4	WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context
transformers	77.8	81.0	75.2	-	-	-	71.9	65.7	77.0	Word Sense Disambiguation with Transformer Models	-
All true	50.8	47.0	53.8	50.8	47.0	53.8	50.8	47.0	53.8	WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context
FastText	53.7	50.6	56.2	52.7	47.7	56.8	53.4	49.0	57.1	WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context
Human	-	-	-	-	-	-	85.3	89.2	82.1	WiC-TSV: An Evaluation Benchmark for Target Sense Verification of Words in Context
CTLR	76.8	79.6	74.5	72.7	81.5	65.6	78.3	85.7	72.1	CTLR@WiC-TSV: Target Sense Verification using Marked Inputs andPre-trained Models	-

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