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Word Sense Disambiguation On Semeval 2007

Metrics

F1

Results

Performance results of various models on this benchmark

Model Name
F1
Paper TitleRepository
LSTMLP (T:SemCor, U:OMSTI)63.7Semi-supervised Word Sense Disambiguation with Neural Models-
SemCor+WNGC, hypernyms73.4Sense Vocabulary Compression through the Semantic Knowledge of WordNet for Neural Word Sense Disambiguation
kNN-BERT60.94Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
SemCor+WNGT, vocabulary reduced, ensemble66.81Improving the Coverage and the Generalization Ability of Neural Word Sense Disambiguation through Hypernymy and Hyponymy Relationships-
LSTM (T:OMSTI)60.7Semi-supervised Word Sense Disambiguation with Neural Models-
LSTMLP (T:OMSTI, U:1K)63.3Semi-supervised Word Sense Disambiguation with Neural Models-
LSTMLP (T:SemCor, U:1K)63.5Semi-supervised Word Sense Disambiguation with Neural Models-
kNN-BERT + POS (training corpus: SemCor)63.17Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings
LSTM (T:SemCor)64.2Semi-supervised Word Sense Disambiguation with Neural Models-
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