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In the current version the export format does not contain an XML replacement of wiki markup (see Wikipedia DTD for an older proposal, or Wiki Markup Language). You only get the wikitext as you get when editing the article. (After export you can use alternative parsers to convert wikitext to other format)
(and the corresponding index file, pages-articles-multistream-index.txt.bz2) pages-articles.xml.bz2 and pages-articles-multistream.xml.bz2 both contain the same xml contents. So if you unpack either, you get the same data. But with multistream, it is possible to get an article from the archive without unpacking the whole thing.
It can open almost any file format. It can export to Mediawiki: File menu > export > save as type > MediaWiki. It will save the file as a .txt file which can be opened with any text editor. Copy the wiki code from the text file. You can save any web page as an HTML file, and then open it in LibreOffice Writer. Edit as needed.
The most efficient way to identify many problems is to go on the individual articles of your book and view the article as a PDF (click "Download as PDF" in the "print/export" box on the left hand side of your screen, towards the bottom). Preview the page, and if something doesn't look right, chances are there's a problem.
The text may be for a completely new article (see Help:New article), or to expand an existing English Wikipedia article. If text is copied over from another Wiki then appropriate attribution must be placed in the edit history of the article (see the guide line Copying within Wikipedia §Translating from other language Wikimedia projects)
Big English–Russian Dictionary; English–French dictionary; Freedict provides a collection of over 85 translating dictionaries, as XML source files with the data, mostly accompanied by databases generated from the XML files in the format used by DICT servers and clients. These are available from the Freedict project web site at. [6] FREELANG ...
The content translation tool assists users in translating existing Wikipedia articles from one language to another. Users select an article in any language, then select another language, and the interface provides machine translation which the human user can then use as inspiration to make readable text in another language.
IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms ...