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Word Sense Disambiguation
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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).
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
On Self-improving Token Embeddings
SANDWiCH: Semantical Analysis of Neighbours for Disambiguating Words in Context ad Hoc
Probing Semantic Routing in Large Mixture-of-Expert Models
TreeMatch: A Fully Unsupervised WSD System Using Dependency Knowledge on a Specific Domain
Fietje: An open, efficient LLM for Dutch
Word Sense Linking: Disambiguating Outside the Sandbox
Can LLMs assist with Ambiguity? A Quantitative Evaluation of various Large Language Models on Word Sense Disambiguation
Astro-HEP-BERT: A bidirectional language model for studying the meanings of concepts in astrophysics and high energy physics
SinaTools: Open Source Toolkit for Arabic Natural Language Processing
How Well Do Large Language Models Disambiguate Swedish Words?
Word Sense Disambiguation in Native Spanish: A Comprehensive Lexical Evaluation Resource
Towards Fairer Health Recommendations: finding informative unbiased samples via Word Sense Disambiguation
ARPA: A Novel Hybrid Model for Advancing Visual Word Disambiguation Using Large Language Models and Transformers
ArabicNLU 2024: The First Arabic Natural Language Understanding Shared Task
To Word Senses and Beyond: Inducing Concepts with Contextualized Language Models
Silent Signals, Loud Impact: LLMs for Word-Sense Disambiguation of Coded Dog Whistles
LexMatcher: Dictionary-centric Data Collection for LLM-based Machine Translation
Word Sense Disambiguation in Persian: Can AI Finally Get It Right?
Multilingual Substitution-based Word Sense Induction
Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?
3AM: An Ambiguity-Aware Multi-Modal Machine Translation Dataset
Neural Sequence-to-Sequence Modeling with Attention by Leveraging Deep Learning Architectures for Enhanced Contextual Understanding in Abstractive Text Summarization
PejorativITy: Disambiguating Pejorative Epithets to Improve Misogyny Detection in Italian Tweets
The LSCD Benchmark: a Testbed for Diachronic Word Meaning Tasks
A Survey on Lexical Ambiguity Detection and Word Sense Disambiguation
Enhancing Modern Supervised Word Sense Disambiguation Models by Semantic Lexical Resources
A Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic Change
Resolving Regular Polysemy in Named Entities
HKUST at SemEval-2023 Task 1: Visual Word Sense Disambiguation with Context Augmentation and Visual Assistance
Improving Word Sense Disambiguation in Neural Machine Translation with Salient Document Context
How Contentious Terms About People and Cultures are Used in Linked Open Data
SALMA: Arabic Sense-Annotated Corpus and WSD Benchmarks
A Survey on Semantic Processing Techniques
Large Language Models and Multimodal Retrieval for Visual Word Sense Disambiguation
Can Word Sense Distribution Detect Semantic Changes of Words?
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