Word Sense Disambiguation On Semeval 2007 1

Métriques

F1

Unsupervised

Résultats

Résultats de performance de divers modèles sur ce benchmark

			Paper Title
SemCor+WNGC, hypernyms	90.4	-	Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation
SemCor+WNGT, vocabulary reduced, ensemble	86.02	-	Improving the Coverage and the Generalization Ability of Neural Word Sense Disambiguation through Hypernymy and Hyponymy Relationships
kNN-BERT + POS (training corpus: WNGT)	85.32	-	Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
LSTMLP (T:SemCor, U:OMSTI)	84.3	-	Semi-supervised Word Sense Disambiguation with Neural Models
LSTMLP (T:SemCor, U:1K)	83.6	-	Semi-supervised Word Sense Disambiguation with Neural Models
LSTMLP (T:OMSTI, U:1K)	83.3	-	Semi-supervised Word Sense Disambiguation with Neural Models
LSTM (T:SemCor)	82.8	-	Semi-supervised Word Sense Disambiguation with Neural Models
ShotgunWSD 2.0	81.22	yes	ShotgunWSD: An unsupervised algorithm for global word sense disambiguation inspired by DNA sequencing
kNN-BERT	81.20	-	Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
LSTM (T:OMSTI)	81.1	-	Semi-supervised Word Sense Disambiguation with Neural Models

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Word Sense Disambiguation On Semeval 2007 1 | SOTA | HyperAI