Results 121 to 130 of about 83,408 (318)
Improving Word Sense Disambiguation with Translations
Conference on Empirical Methods in Natural Language Processing, 2020 It has been conjectured that multilingual information can help monolingual word sense disambiguation (WSD). However, existing WSD systems rarely consider multilingual information, and no effective method has been proposed for improving WSD by generating ...
Yixing Luan +3 more
semanticscholar +1 more source
Transactions of the Philological Society, EarlyView.Abstract This study investigates the lexicographical potential of Medieval Latin documentation from the Venetian area of the Italo‐Romance domain, highlighting the need for a systematic approach to bridge Latin and vernacular linguistic developments. The project MEDITA – Medieval Latin Documentation and Digital Italo‐Romance Lexicography.
Jacopo Gesiot
wiley +1 more source
Composing senselessness: Autoethnography after homicide
Anthropology and Humanism, EarlyView.Abstract Not all narratives create meaning, or create the same kinds of meaning; instead, some stories amplify meaninglessness, which—it is argued—is its own form of sense‐making. This article examines how meaning is formulated through narrative in the absence of a meaningful death, specifically in the context of a motiveless murder.
Jerome Arrow
wiley +1 more source
A concept-based adaptive approach to word sense disambiguation [PDF]
, 1998 Jen Nan Chen, Jason S. Chang
openalex +2 more sources
Toward Universal Word Sense Disambiguation Using Deep Neural Networks
IEEE Access, 2019 Traditionally, approaches based on neural networks to solve the problem of disambiguation of the meaning of words (WSD) use a set of classifiers at the end, which results in a specialization in a single set of words-those for which they were trained ...
Hiram Calvo +3 more
doaj +1 more source
Journal of Language ModellingWe develop a three-part approach to Verb Sense Disambiguation (VSD) in German. After considering a set of lexical resources and corpora, we arrive at a statistically motivated selection of a subset of verbs and their senses from GermaNet.
Dominik Mattern +3 more
doaj +2 more sources
Neural Sequence Learning Models for Word Sense Disambiguation
Conference on Empirical Methods in Natural Language Processing, 2017 Word Sense Disambiguation models exist in many flavors. Even though supervised ones tend to perform best in terms of accuracy, they often lose ground to more flexible knowledge-based solutions, which do not require training by a word expert for every ...
Alessandro Raganato +2 more
semanticscholar +1 more source
Business Ethics, the Environment &Responsibility, EarlyView.ABSTRACT This study examines how individuals accept and navigate paradoxical tensions within a sustainability context, using a multiple case study of five Italian companies implementing circularity measurement tools. By exploring the interplay between self‐efficacy and acceptance of paradoxical tensions, drawing upon the Goal Setting and Paradox ...
Alice Alosi +4 more
wiley +1 more source
An Optimized Lesk-Based Algorithm for Word Sense Disambiguation
Open Computer Science, 2016 Computational complexity is a characteristic of almost all Lesk-based algorithms for word sense disambiguation (WSD). In this paper, we address this issue by developing a simple and optimized variant of the algorithm using topic composition in documents ...
Ayetiran Eniafe Festus, Agbele Kehinde
doaj +1 more source
Sometimes less is more : Romanian word sense disambiguation revisited [PDF]
, 2007 Recent approaches to Word Sense Disambiguation (WSD) generally fall into two classes: (1) information-intensive approaches and (2) information-poor approaches.
Dinu, Georgiana, Kübler, Sandra
core