SOTAVerified

Hypernym Discovery

Given a corpus and a target term (hyponym), the task of hypernym discovery consists of extracting a set of its most appropriate hypernyms from the corpus. For example, for the input word “dog”, some valid hypernyms would be “canine”, “mammal” or “animal”.

Papers

Showing 110 of 33 papers

TitleStatusHype
Hyperbolic Entailment Cones for Learning Hierarchical EmbeddingsCode1
OntoTune: Ontology-Driven Self-training for Aligning Large Language ModelsCode1
TaxoLLaMA: WordNet-based Model for Solving Multiple Lexical Semantic TasksCode1
Exploiting Multiple Sources for Open-Domain Hypernym Discovery0
Analyzing BERT’s Knowledge of Hypernymy via Prompting0
300-sparsans at SemEval-2018 Task 9: Hypernymy as interaction of sparse attributes0
BabelDomains: Large-Scale Domain Labeling of Lexical Resources0
Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection0
Document Structure aware Relational Graph Convolutional Networks for Ontology Population0
Apollo at SemEval-2018 Task 9: Detecting Hypernymy Relations Using Syntactic Dependencies0
Show:102550
← PrevPage 1 of 4Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CRIMMAP19.78Unverified
2vTEMAP10.6Unverified
3NLP_HZMAP9.37Unverified
4300-sparsansMAP8.95Unverified
5MFHMAP8.77Unverified
6SJTU BCMIMAP5.77Unverified
7ApolloMAP2.68Unverified
8balAPIncMAP1.36Unverified
#ModelMetricClaimedVerifiedStatus
1CRIMMAP34.05Unverified
2MFHMAP28.93Unverified
3300-sparsansMAP20.75Unverified
4vTEMAP18.84Unverified
5EXPRMAP13.77Unverified
6SJTU BCMIMAP11.69Unverified
7ADAPTMAP8.13Unverified
8balAPIncMAP0.91Unverified
#ModelMetricClaimedVerifiedStatus
1CRIMMAP40.97Unverified
2MFHMAP33.32Unverified
3300-sparsansMAP29.54Unverified
4vTEMAP12.99Unverified
5SJTU BCMIMAP4.71Unverified
6ADAPTMAP2.63Unverified
7balAPIncMAP1.95Unverified