SOTAVerified

Word Sense Induction

Word sense induction (WSI) is widely known as the “unsupervised version” of WSD. The problem states as: Given a target word (e.g., “cold”) and a collection of sentences (e.g., “I caught a cold”, “The weather is cold”) that use the word, cluster the sentences according to their different senses/meanings. We do not need to know the sense/meaning of each cluster, but sentences inside a cluster should have used the target words with the same sense.

Description from NLP Progress

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–100 of 107 papers

TitleStatusHype
Finding Individual Word Sense Changes and their Delay in Appearance—0
From the Culinary to the Political Meaning of ``quenelle'' : Using Topic Models For Identifying Novel Senses (De la quenelle culinaire \`a la quenelle politique : identification de changements s\'emantiques \`a l'aide des Topic Models) [in French]—0
Graph-Based Induction of Word Senses in Croatian—0
How much does a word weigh? Weighting word embeddings for word sense induction—0
Improved Estimation of Entropy for Evaluation of Word Sense Induction—0
Inducing Word Sense with Automatically Learned Hidden Concepts—0
Large Scale Substitution-based Word Sense Induction—0
Learning Sense-specific Word Embeddings By Exploiting Bilingual Resources—0
Leveraging Lexical Substitutes for Unsupervised Word Sense Induction—0
LIMSI : Cross-lingual Word Sense Disambiguation using Translation Sense Clustering—0
Mixing in Some Knowledge: Enriched Context Patterns for Bayesian Word Sense Induction—0
Multilingual Substitution-based Word Sense Induction—0
Naive Bayes Word Sense Induction—0
Navigating the Semantic Horizon using Relative Neighborhood Graphs—0
Neural context embeddings for automatic discovery of word senses—0
One Million Sense-Tagged Instances for Word Sense Disambiguation and Induction—0
One Sense per Tweeter ... and Other Lexical Semantic Tales of Twitter—0
On Modeling Sense Relatedness in Multi-prototype Word Embedding—0
Parsing with Context Embeddings—0
Paving the Way to a Large-scale Pseudosense-annotated Dataset—0
Regular polysemy: A distributional model—0
Retrofitting Word Representations for Unsupervised Sense Aware Word Similarities—0
RUSSE'2018: A Shared Task on Word Sense Induction for the Russian Language—0
SATTY : Word Sense Induction Application in Web Search Clustering—0
Semantic clustering of Russian web search results: possibilities and problems—0
SemEval-2013 Task 11: Word Sense Induction and Disambiguation within an End-User Application—0
SemEval-2013 Task 13: Word Sense Induction for Graded and Non-Graded Senses—0
Sense Embedding Learning for Word Sense Induction—0
Structured Generative Models of Continuous Features for Word Sense Induction—0
Supervised and unsupervised approaches to measuring usage similarity—0
The brWaC Corpus: A New Open Resource for Brazilian Portuguese—0
The LSCD Benchmark: a Testbed for Diachronic Word Meaning Tasks—0
Topological Data Analysis for Word Sense Disambiguation—0
Topology of Word Embeddings: Singularities Reflect Polysemy—0
Towards Dynamic Word Sense Discrimination with Random Indexing—0
Absinth: A small world approach to word sense induction—0
UKP-WSI: UKP Lab Semeval-2013 Task 11 System Description—0
unimelb: Topic Modelling-based Word Sense Induction for Web Snippet Clustering—0
Unsupervised Does Not Mean Uninterpretable: The Case for Word Sense Induction and Disambiguation—0
Unsupervised Estimation of Word Usage Similarity—0
A Simple Approach to Learn Polysemous Word EmbeddingsCode0
Exploring Topic Coherence over Many Models and Many TopicsCode0
Watset: Automatic Induction of Synsets from a Graph of SynonymsCode0
A Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic ChangeCode0
Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly PublicationsCode0
Automated WordNet Construction Using Word EmbeddingsCode0
An Evaluation Method for Diachronic Word Sense InductionCode0
How does BERT capture semantics? A closer look at polysemous wordsCode0
UoB at SemEval-2020 Task 1: Automatic Identification of Novel Word SensesCode0
AutoSense Model for Word Sense InductionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BERT+DPF-Score71.3—Unverified
2AutoSenseF-Score61.7—Unverified
3LDAF-Score60.7—Unverified
4SE-WSI-fixF-Score55.1—Unverified
5BNP-HCF-Score23.1—Unverified