SOTAVerified

Word Sense Disambiguation

The task of Word Sense Disambiguation (WSD) consists of associating words in context with their most suitable entry in a pre-defined sense inventory. The de-facto sense inventory for English in WSD is WordNet.. For example, given the word “mouse” and the following sentence:

“A mouse consists of an object held in one's hand, with one or more buttons.”

we would assign “mouse” with its electronic device sense (the 4th sense in the WordNet sense inventory).

Papers

Showing 51–100 of 1035 papers

TitleStatusHype
Addressing polysemy in bilingual lexicon extraction from comparable corpora—0
A Broad Evaluation of Techniques for Automatic Acquisition of Multiword Expressions—0
Addressing Cross-Lingual Word Sense Disambiguation on Low-Density Languages: Application to Persian—0
A Layered Language Model based Hybrid Approach to Automatic Full Diacritization of Arabic—0
Adding Distributional Semantics to Knowledge Base Entities through Web-scale Entity Linking—0
A Comparative Study of Transformers on Word Sense Disambiguation—0
Aligning Verb Senses in Two Italian Lexical Semantic Resources—0
Alignment-based sense selection in METEOR and the RATATOUILLE recipe—0
All-words Word Sense Disambiguation Using Concept Embeddings—0
A Long Short-Term Memory Model for Answer Sentence Selection in Question Answering—0
Ambiguity Diagnosis for Terms in Digital Humanities—0
Addressing Problems across Linguistic Levels in SMT: Combining Approaches to Model Morphology, Syntax and Lexical Choice—0
Abduction for Discourse Interpretation: A Probabilistic Framework—0
A Large-Scale Pseudoword-Based Evaluation Framework for State-of-the-Art Word Sense Disambiguation—0
A Large DataBase of Hypernymy Relations Extracted from the Web.—0
A Dataset of Translational Equivalents Built on the Basis of plWordNet-Princeton WordNet Synset Mapping—0
A Large Automatically-Acquired All-Words List of Multiword Expressions Scored for Compositionality—0
A language-independent LESK based approach to Word Sense Disambiguation—0
Adapting VerbNet to French using existing resources—0
A Comparative Evaluation of Word Sense Disambiguation Algorithms for German—0
A Knowledge-Based Approach to Word Sense Disambiguation by distributional selection and semantic features—0
Anota \~ao de corpus com a OpenWordNet-PT: um exerc\' de desambigua \~ao (Sense annotation with OpenWordNet-PT: an exercise of word sense disambiguation)—0
A Joint Sequential and Relational Model for Frame-Semantic Parsing—0
A Java Framework for Multilingual Definition and Hypernym Extraction—0
An Iterative `Sudoku Style' Approach to Subgraph-based Word Sense Disambiguation—0
AI-KU: Using Co-Occurrence Modeling for Semantic Similarity—0
Adapting the TTL Romanian POS Tagger to the Biomedical Domain—0
A Cohesive Distillation Architecture for Neural Language Models—0
A picture is worth a thousand words: Using OpenClipArt library for enriching IndoWordNet—0
A Hybrid Distributional and Knowledge-based Model of Lexical Semantics—0
A Hybrid Approach to Word Sense Disambiguation Combining Supervised and Unsupervised Learning—0
Accounting ngrams and multi-word terms can improve topic models—0
A Hybrid Approach for Deep Machine Translation—0
A New Semantic Lexicon and Similarity Measure in Bangla—0
A new semantically annotated corpus with syntactic-semantic and cross-lingual senses—0
A Hierarchical Semantics-Aware Distributional Similarity Scheme—0
A Corpus of Literal and Idiomatic Uses of German Infinitive-Verb Compounds—0
A Bayesian model for joint word alignment and part-of-speech transfer—0
An Eye-tracking Study of Named Entity Annotation—0
An Improved Approach for Word Ambiguity Removal—0
An Improved Crowdsourcing Based Evaluation Technique for Word Embedding Methods—0
A New Minimally-Supervised Framework for Domain Word Sense Disambiguation—0
An Inventory of Preposition Relations—0
An Iterative Approach for Unsupervised Most Frequent Sense Detection using WordNet and Word Embeddings—0
A New Approach to Animacy Detection—0
Annotating the MASC Corpus with BabelNet—0
Annotation for annotation - Toward eliciting implicit linguistic knowledge through annotation - (Project Note)—0
An Open-source Framework for Multi-level Semantic Similarity Measurement—0
A good space: Lexical predictors in word space evaluation—0
An Evaluation of Image-Based Verb Prediction Models against Human Eye-Tracking Data—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1COSINE + Transductive LearningAccuracy85.3—Unverified
2PaLM 540B (finetuned)Accuracy78.8—Unverified
3ST-MoE-32B 269B (fine-tuned)Accuracy77.7—Unverified
4DeBERTa-EnsembleAccuracy77.5—Unverified
5Vega v2 6B (fine-tuned)Accuracy77.4—Unverified
6UL2 20B (fine-tuned)Accuracy77.3—Unverified
7Turing NLR v5 XXL 5.4B (fine-tuned)Accuracy77.1—Unverified
8T5-XXL 11BAccuracy76.9—Unverified
9DeBERTa-1.5BAccuracy76.4—Unverified
10ST-MoE-L 4.1B (fine-tuned)Accuracy74—Unverified
#ModelMetricClaimedVerifiedStatus
1SANDWiCHSenseval 287.8—Unverified
2GlossGPTSenseval 286.1—Unverified
3ConSeC+WNGCSenseval 282.7—Unverified
4ESR+WNGCSenseval 282.5—Unverified
5ConSeCSenseval 282.3—Unverified
6ESCHER SemCorSenseval 281.7—Unverified
7ESRSenseval 281.3—Unverified
8EWISER+WNGCSenseval 280.8—Unverified
9SemCor+WNGC, hypernymsSenseval 279.7—Unverified
10SparseLMMS+WNGCSenseval 279.6—Unverified
#ModelMetricClaimedVerifiedStatus
1Human BenchmarkAccuracy0.81—Unverified
2ruT5-large-finetuneAccuracy0.74—Unverified
3RuBERT conversationalAccuracy0.73—Unverified
4RuBERT plainAccuracy0.73—Unverified
5ruRoberta-large finetuneAccuracy0.72—Unverified
6ruBert-base finetuneAccuracy0.71—Unverified
7Multilingual BertAccuracy0.69—Unverified
8ruT5-base-finetuneAccuracy0.68—Unverified
9ruBert-large finetuneAccuracy0.68—Unverified
10SBERT_Large_mt_ru_finetuningAccuracy0.66—Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF178.7—Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF172.63—Unverified
3LSTMLP (T:SemCor, U:1K)F169.5—Unverified
4LSTMLP (T:OMSTI, U:1K)F168.1—Unverified
5LSTMLP (T:SemCor, U:OMSTI)F167.9—Unverified
6LSTM (T:OMSTI)F167.3—Unverified
7GASext (Concatenation)F167.2—Unverified
8GASext (Linear)F167.1—Unverified
9GAS (Concatenation)F167—Unverified
10LSTM (T:SemCor)F167—Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF179.7—Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF175.15—Unverified
3LSTMLP (T:OMSTI, U:1K)F174.4—Unverified
4LSTMLP (T:SemCor, U:OMSTI)F173.9—Unverified
5LSTMLP (T:SemCor, U:1K)F173.8—Unverified
6LSTM (T:SemCor)F173.6—Unverified
7GASext (Linear)F172.4—Unverified
8LSTM (T:OMSTI)F172.4—Unverified
9GASext (Concatenation)F172.2—Unverified
10GAS (Concatenation)F172.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF177.8—Unverified
2LSTMLP (T:SemCor, U:1K)F171.8—Unverified
3LSTMLP (T:SemCor, U:OMSTI)F171.1—Unverified
4LSTMLP (T:OMSTI, U:1K)F171—Unverified
5GASext (Concatenation)F170.5—Unverified
6GAS (Concatenation)F170.2—Unverified
7SemCor+WNGT, vocabulary reduced, ensembleF170.11—Unverified
8GASext (Linear)F170.1—Unverified
9GAS (Linear)F170—Unverified
10LSTM (T:SemCor)F169.2—Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF190.4—Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF186.02—Unverified
3kNN-BERT + POS (training corpus: WNGT)F185.32—Unverified
4LSTMLP (T:SemCor, U:OMSTI)F184.3—Unverified
5LSTMLP (T:SemCor, U:1K)F183.6—Unverified
6LSTMLP (T:OMSTI, U:1K)F183.3—Unverified
7LSTM (T:SemCor)F182.8—Unverified
8ShotgunWSD 2.0F181.22—Unverified
9kNN-BERTF181.2—Unverified
10LSTM (T:OMSTI)F181.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF173.4—Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF166.81—Unverified
3LSTM (T:SemCor)F164.2—Unverified
4LSTMLP (T:SemCor, U:OMSTI)F163.7—Unverified
5LSTMLP (T:SemCor, U:1K)F163.5—Unverified
6LSTMLP (T:OMSTI, U:1K)F163.3—Unverified
7kNN-BERT + POS (training corpus: SemCor)F163.17—Unverified
8kNN-BERTF160.94—Unverified
9LSTM (T:OMSTI)F160.7—Unverified
#ModelMetricClaimedVerifiedStatus
1GlossGPTF1 (Zeroshot Dev)81.8—Unverified
2ESR LargeF1 (Zeroshot Dev)77.4—Unverified
3ESR baseF1 (Zeroshot Dev)73.9—Unverified
4SEMEq LargeF1 (Zeroshot Dev)73.7—Unverified
5SEMeq baseF1 (Zeroshot Dev)71.5—Unverified
6RTWE largeF1 (Zero shot test)69.9—Unverified
7LeskF1 (Zeroshot Dev)40.1—Unverified
8MFSF1 (Zeroshot Dev)0—Unverified
#ModelMetricClaimedVerifiedStatus
1HumanTask 3 Accuracy: all85.3—Unverified
2transformersTask 1 Accuracy: all77.8—Unverified
3CTLRTask 1 Accuracy: all76.8—Unverified
4GlossBert-wsTask 1 Accuracy: all75.9—Unverified
5Bert-baseTask 1 Accuracy: all75.3—Unverified
6Unsupervised BertTask 1 Accuracy: all54.4—Unverified
7FastTextTask 1 Accuracy: all53.7—Unverified
8All trueTask 1 Accuracy: all50.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy69.1—Unverified
2Gopher-280B (few-shot, k=5)Accuracy56.4—Unverified
3OPT 175BAccuracy49.1—Unverified
4GAL 120B (few-shot, k=5)Accuracy48.7—Unverified
5GAL 30B (few-shot, k=5)Accuracy47—Unverified
6BLOOM 176BAccuracy1.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UKBppr_w2wSenseval 268.8—Unverified
2KEFAll68—Unverified
3WSD-TMAll66.9—Unverified
4BabelfyAll65.5—Unverified
5WN 1st sense baselineAll65.2—Unverified
6UKBppr_w2w-nfAll57.5—Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF182.6—Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF174.46—Unverified
3GASext (Concatenation)F172.6—Unverified
4GASext (Linear)F172.1—Unverified
5GAS (Concatenation)F171.8—Unverified
6GAS (Linear)F171.6—Unverified
#ModelMetricClaimedVerifiedStatus
1kNN-BERTF180.12—Unverified
2IMS + adapted CWF173.4—Unverified
3BiLSTM with GloVeF173.4—Unverified
4Single BiLSTMF172.5—Unverified
#ModelMetricClaimedVerifiedStatus
1kNN-BERTF176.52—Unverified
2BiLSTM with GloVeF166.9—Unverified
3IMS + adapted CWF166.2—Unverified
#ModelMetricClaimedVerifiedStatus
1SPINSequence Recovery %(All)30.3—Unverified