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Subjectivity word sense disambiguation [PDF]
This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. We provide empirical evidence that SWSD is more feasible than full word sense disambiguation, and that it can be ...
Janyce Wiebe, Rada Mihalcea, Cem Akkaya
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A review of word-sense disambiguation methods and algorithms: Introduction
The word-sense disambiguation task is a classification task, where the goal is to predict the meaning of words and phrases with the help of surrounding text.
Tatiana Kaushinis+14 more
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Abstract This review examines the role of open citations in fostering transparency, reproducibility, and accessibility in scholarly communication. Through a critical synthesis of diverse sources—articles, proceedings, presentations, datasets, and blog posts—it explores the motivations behind citing, the evolving meanings of citations, and key ...
Zehra Taşkın
wiley +1 more source
From Word Alignment to Word Senses, via Multilingual Wordnets [PDF]
Most of the successful commercial applications in language processing (text and/or speech) dispense with any explicit concern on semantics, with the usual motivations stemming from the computational high costs required for dealing with semantics, in case
Dan Tufis
doaj
Abstract The term semantic primitives refers to a set of basic, atomic concepts from which all other (compound) concepts are constructed. It presupposes the principle of compositionality—the idea that complex items or expressions can be formed by combining simpler constituents.
Birger Hjørland
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Nibbling at the Hard Core of Word Sense Disambiguation
With state-of-the-art systems having finally attained estimated human performance, Word Sense Disambiguation (WSD) has now joined the array of Natural Language Processing tasks that have seemingly been solved, thanks to the vast amounts of knowledge encoded into Transformer-based pre-trained language models. And yet, if we look below the surface of raw
Maru, Marco+3 more
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Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources
Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources Lexical resources can be applied in many different Natural Language Engineering tasks, but the most fundamental task is the recognition of word senses used in ...
Paweł Kędzia+2 more
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ABSTRACT Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder associated with episodic memory impairment. Although emotional factors such as arousal, as well as age and depression symptoms, are known to influence episodic memory in neurotypical (NT) populations, how these factors affect memory processes in ASD, which is associated ...
Sidni A. Justus+3 more
wiley +1 more source
Capsule Network Improved Multi-Head Attention for Word Sense Disambiguation
Word sense disambiguation (WSD) is one of the core problems in natural language processing (NLP), which is to map an ambiguous word to its correct meaning in a specific context.
Jinfeng Cheng, Weiqin Tong, Weian Yan
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Under‐Interpretation of Neuroimaging Data in Insanity Assessment: A Hidden Risk
ABSTRACT Neuroimaging data can provide valuable insights into insanity evaluations, but the debate over its use for legal purposes is far from resolved. While much attention has been given to the risks of over‐interpretation, potential errors stemming from under‐interpretation received less scrutiny. In this paper, we aim to showcase how this error may
Camilla Frangi+5 more
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