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Word sense disambiguation (WSD) plays a crucial role in natural language processing. Unsupervised WSD approaches based on knowledge bases like HowNet offer improved applicability compared to supervised learning, but existing research tends to ...

Machine translation systems have penetrated our daily lives, providing translation services from source language to target language to millions of users online daily. Word Sense Disambiguation (WSD) is one of the essential functional requirements of ...

Databases systems are used almost everywhere in modern life and a prior knowledge of query languages like SQL is required to interact with these systems. Generally, relational databases are very useful for storing a significant amount of the world’...

Word Sense Disambiguation (WSD) which aims to identify the correct sense of a target word appearing in a specific context is essential for web text analysis. The use of glosses has been explored as a means for WSD. However, only a few works model the ...

Representation of knowledge and making it machine comprehensible has become a necessity in modern times but with the large amount of data being generated nowadays, this process has to be automated as much as possible. In this work, we propose a ...

This study aims to demonstrate the methods for detecting negations in a sentence by uniquely evaluating the lexical structure of the text via word-sense disambiguation. The proposed framework examines all the unique features in the various expressions ...

Representation learning is an important component in solving most Natural Language Processing (NLP) problems, including Word Sense Disambiguation (WSD). The WSD task tries to find the best meaning in a knowledge base for a word with multiple meanings (...

Word Sense Disambiguation (WSD), the process of automatically identifying the correct meaning of a word used in a given context, is a significant challenge in Natural Language Processing. A range of approaches to the problem has been explored by the ...

Pun location is to identify the punning word (usually a word or a phrase that makes the text ambiguous) in a given short text, and pun interpretation is to find out two different meanings of the punning word. Most previous studies adopt limited ...

Modern transformer-based neural architectures yield impressive results in nearly every NLP task and Word Sense Disambiguation, the problem of discerning the correct sense of a word in a given context, is no exception. State-of-the-art approaches ...

In this paper, we unify a diverse set of learning tasks in NLP, semantic retrieval and related areas, under a common umbrella, which we call unsupervised semantic association learning (USAL). Examples of this generic task include word sense ...

Many downstream NLP tasks have shown significant improvement through continual pre-training, transfer learning and multi-task learning. State-of-the-art approaches in Word Sense Disambiguation today benefit from some of these approaches in ...

The limited amount of the sense annotated data is a big challenge for the word sense disambiguation task. As a solution to this problem, we propose an algorithm of automatic generation and labelling of the training collections based on the ...

Word Sense Disambiguation (WSD) is the task of associating the correct meaning with a word in a given context. WSD provides explicit semantic information that is beneficial to several downstream applications, such as question answering,...

Definitional knowledge has proved to be essential in various Natural Language Processing tasks and applications, especially when information at the level of word senses is exploited. However, the few sense-annotated corpora of textual definitions ...

Word Sense Disambiguation (WSD) is the process of determining which sense of a word is used in a given context. Most of Arabic WSD systems are based generally on the information extracted from the local context of the word to be disambiguated by ...

Corpus based natural language processing has emerged with great success in recent years. It is not only used for languages like English, French, Spanish, and Hindi but also is widely used for languages like Tamil, Telugu etc. This paper focuses to ...

Word Sense Disambiguation (WSD) is a task which aims to identify the meaning of a word given its context. This problem has been investigated and analyzed in depth in English. However, work in Arabic has been limited despite the fact that there are ...

Word Sense Disambiguation represents a crucial task in many natural language processing applications such as information extraction, information retrieval and text summarization. It intends to identify the correct sense of an ambiguous term (target word)...

Emotions can be judged by a combination of cues such as speech facial expressions and actions. Emotions are also articulated by text. This paper shows a new hybrid model for detecting emotion from text which depends on ontology with keywords semantic ...