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Truecasing

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This is an old revision of this page, as edited by Your Lord and Master (talk | contribs) at 01:03, 3 October 2010 (Added {{essay-like}} and {{unreferenced}} tags to article using TW). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Truecasing is the problem in natural language processing (NLP) of determining the proper capitalization of words where such information is unavailable. This commonly comes up due to the standard practice (in English and many other languages) of automatically capitalizing the first word of a sentence. It can also arise in badly-cased or noncased text (for example, all-lowercase or all-uppercase text messages). Truecasing aids in many other NLP tasks, such as named entity recognition, machine translation and automatic content extraction.

Truecasing is unnecessary in languages whose scripts do not have a distinction between uppercase and lowercase letters. This includes all languages not written in the Latin, Greek or Cyrillic scripts, such as Japanese, Chinese, Thai, Hebrew, Arabic, Hindi, etc.