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 125 of 33 papers

TitleStatusHype
OntoTune: Ontology-Driven Self-training for Aligning Large Language ModelsCode1
TaxoLLaMA: WordNet-based Model for Solving Multiple Lexical Semantic TasksCode1
Probing Pretrained Language Models with Hierarchy Properties0
Modelling Commonsense Properties using Pre-Trained Bi-EncodersCode0
HyperBox: A Supervised Approach for Hypernym Discovery using Box Embeddings0
CogALex 2.0: Impact of Data Quality on Lexical-Semantic Relation PredictionCode0
Analyzing BERT’s Knowledge of Hypernymy via Prompting0
Hypernym Discovery via a Recurrent Mapping Model0
Document Structure aware Relational Graph Convolutional Networks for Ontology Population0
CogALex-VI Shared Task: Transrelation - A Robust Multilingual Language Model for Multilingual Relation IdentificationCode0
Meemi: A Simple Method for Post-processing and Integrating Cross-lingual Word Embeddings0
The Effectiveness of Simple Hybrid Systems for Hypernym Discovery0
Document Structure Measure for Hypernym discovery0
Learning Scalar Adjective Intensity from Paraphrases0
300-sparsans at SemEval-2018 Task 9: Hypernymy as interaction of sparse attributes0
EXPR at SemEval-2018 Task 9: A Combined Approach for Hypernym Discovery0
UMDuluth-CS8761 at SemEval-2018 Task9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings0
CRIM at SemEval-2018 Task 9: A Hybrid Approach to Hypernym DiscoveryCode0
NLP\_HZ at SemEval-2018 Task 9: a Nearest Neighbor Approach0
Apollo at SemEval-2018 Task 9: Detecting Hypernymy Relations Using Syntactic Dependencies0
SemEval-2018 Task 9: Hypernym Discovery0
ADAPT at SemEval-2018 Task 9: Skip-Gram Word Embeddings for Unsupervised Hypernym Discovery in Specialised Corpora0
SJTU-NLP at SemEval-2018 Task 9: Neural Hypernym Discovery with Term Embeddings0
UMDuluth-CS8761 at SemEval-2018 Task 9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings0
Tel(s)-Telle(s)-Signs: Highly Accurate Automatic Crosslingual Hypernym Discovery0
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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