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However, where the subject of an article is best known in English-language sources by its non-English name (e.g., Taj Mahal, Champs-Élysées), the non-English title may be appropriate for the article. Relevant non-English names, such as those of people who do not write their names in English, are encouraged. If the subject of the article is ...
No-output templates that indicate the article's established date format and English-language variety, if any (e.g., {{Use dmy dates}}, {{Use Canadian English}}) Banner-type maintenance templates, Dispute and Cleanup templates for article-wide issues that have been flagged (otherwise used at the top of a specific section, after any sectional ...
Wikipedia articles therefore tend to have a higher citation density than research articles and survey articles. In a research article, much of the content is likely to be original and unsourced, and even in a survey article, you would probably feel free to make up small unsourced derivations that are more than a trivial calculation but that are ...
A thesaurus is composed by at least three elements: 1-a list of words (or terms), 2-the relationship amongst the words (or terms), indicated by their hierarchical relative position (e.g. parent/broader term; child/narrower term, synonym, etc.), 3-a set of rules on how to use the thesaurus.
Although the content of an article is more important than the format, it is customary for scientific articles to follow a standard structure, which varies only slightly in different subjects. Although the IMRAD structure emphasizes the organization of content, and in scientific journal articles, each section (Introduction, Methods, Results, and ...
Articles start with a lead section (WP:CREATELEAD) summarising the most important points of the topic.The lead section is the first part of the article; it comes above the first header, and may contain a lead image which is representative of the topic, and/or an infobox that provides a few key facts, often statistical, such as dates and measurements.
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WordNet is the most commonly used computational lexicon of English for word-sense disambiguation (WSD), a task aimed at assigning the context-appropriate meanings (i.e. synset members) to words in a text. [13]