Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders [PDF]
A major obstacle in Word Sense Disambiguation (WSD) is that word senses are not uniformly distributed, causing existing models to generally perform poorly on senses that are either rare or unseen during training.
Terra Blevins, Luke Zettlemoyer
semanticscholar +5 more sources
Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation
The Word Sense Disambiguation system is widely used in many fields, including business, research, education, and government organizations. The availability of natural language data on the internet has grown in tandem with the rapid advancement of ...
Surbhi Bhatia +2 more
doaj +2 more sources
Lexical Chain dan Word Sense Disambiguation Untuk Peringkasan Artikel Berbahasa Indonesia
Text Summarization adalah sebuah proses untuk menghasilkan ringkasan suatu dokumen dengan tidak menghilangkan informasi utama dari artikel. Ada beberapa metode untuk melakukan peringkasan, seperti metode rantai leksikal atau lexical chain yang memiliki ...
Dika Muhammad Fazar +1 more
doaj +3 more sources
Application of the transformer model algorithm in chinese word sense disambiguation: a case study in chinese language [PDF]
This study aims to explore the research methodology of applying the Transformer model algorithm to Chinese word sense disambiguation, seeking to resolve word sense ambiguity in the Chinese language.
Linlin Li +3 more
doaj +2 more sources
Harmony Search Algorithm for Word Sense Disambiguation. [PDF]
Word Sense Disambiguation (WSD) is the task of determining which sense of an ambiguous word (word with multiple meanings) is chosen in a particular use of that word, by considering its context.
Saad Adnan Abed +2 more
doaj +2 more sources
Multilingual Word Sense Disambiguation with Unified Sense Representation [PDF]
As a key natural language processing (NLP) task, word sense disambiguation (WSD) evaluates how well NLP models can understand the fine-grained semantics of words under specific contexts. Benefited from the large-scale annotation, current WSD systems have
Ying Su +3 more
openalex +3 more sources
AMuSE-WSD: An All-in-one Multilingual System for Easy Word Sense Disambiguation [PDF]
Over the past few years, Word Sense Disambiguation (WSD) has received renewed interest: recently proposed systems have shown the remarkable effectiveness of deep learning techniques in this task, especially when aided by modern pretrained language models.
Riccardo Orlando +4 more
openalex +2 more sources
Entity Linking meets Word Sense Disambiguation: a Unified Approach
Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental respect: in EL the textual mention can be linked to a named entity which may ...
Andrea Moro +2 more
doaj +2 more sources
XL-WSD: An Extra-Large and Cross-Lingual Evaluation Framework for Word Sense Disambiguation
Transformer-based architectures brought a breeze of change to Word Sense Disambiguation (WSD), improving models' performances by a large margin. The fast development of new approaches has been further encouraged by a well-framed evaluation suite for ...
Tommaso Pasini +2 more
openalex +3 more sources
Word sense disambiguation using hybrid swarm intelligence approach. [PDF]
Word sense disambiguation (WSD) is the process of identifying an appropriate sense for an ambiguous word. With the complexity of human languages in which a single word could yield different meanings, WSD has been utilized by several domains of interests ...
Wafaa Al-Saiagh +4 more
doaj +2 more sources

