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2. Template:Number to word - Wikipedia

   en.wikipedia.org/wiki/Template:Number_to_word

   This template is used in MediaWiki:Watchlist-messages, and on approximately 8,000 pages. Changes to it can cause immediate changes to the Wikipedia user interface. To avoid major disruption, any changes should be tested in the template's /sandbox or /testcases subpages, or in your own user subpage.

3. PDFtk - Wikipedia

   en.wikipedia.org/wiki/Pdftk

   PDFtk (short for PDF Toolkit) is a toolkit for manipulating Portable Document Format (PDF) documents. [3] [4] It runs on Linux, Windows and macOS. [5] It comes in three versions: PDFtk Server (open-source command-line tool), PDFtk Free and PDFtk Pro (proprietary paid). [2] It is able to concatenate, shuffle, split and rotate PDF files.

4. Poppler (software) - Wikipedia

   en.wikipedia.org/wiki/Poppler_(software)

   Poppler is a free and open-source software library for rendering Portable Document Format (PDF) documents. Its development is supported by freedesktop.org . Commonly used on Linux systems, [ 4 ] it powers the PDF viewers of the GNOME and KDE desktop environments .

5. Category:Numbers as words conversion templates - Wikipedia

   en.wikipedia.org/wiki/Category:Numbers_as_words...

   [[Category:Numbers as words conversion templates]] to the <includeonly> section at the bottom of that page. Otherwise, add <noinclude>[[Category:Numbers as words conversion templates]]</noinclude> to the end of the template code, making sure it starts on the same line as the code's last character.

6. Interlinear gloss - Wikipedia

   en.wikipedia.org/wiki/Interlinear_gloss

   When glossed, each line of the original text acquires one or more corresponding lines of transcription known as an interlinear text or interlinear glossed text (IGT) – an interlinear for short. Such glosses help the reader follow the relationship between the source text and its translation, and the structure of the original language.

7. Word2vec - Wikipedia

   en.wikipedia.org/wiki/Word2vec

   Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus.