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GIFT allows someone to use a text editor to write multiple-choice, true-false, short answer, matching, missing word and numerical questions in a simple format that can be imported to a computer-based quizzes. The content is an UTF-8-encoded text file. Example:
Browser-based AI tool that automatically convert any docx or pdf quiz or exam into QTI. Does not require pdf or word document to conform to any specific format. Supports exports to QTI 2.1, QTI 1.2, Blackboard Pool, Google Classroom and Moodle XML. Proprietary: No GradeMaker: 2.1, 2.2
Open your document in Word, and "save as" an HTML file. Open the HTML file in a text editor and copy the HTML source code to the clipboard. Paste the HTML source into the large text box labeled "HTML markup:" on the html to wiki page. Click the blue Convert button at the bottom of the page.
When satisfied that the sandbox convert template is performing correctly, it can be used to replace Template:Convert. Other pages are needed, but the above is all that is required in order to have a working convert template.
The term template, when used in the context of word processing software, refers to a sample document that has already some details in place; those can (that is added/completed, removed or changed, differently from a fill-in-the-blank of the approach as in a form) either by hand or through an automated iterative process, such as with a software assistant.
The {} template and its variants support all ISO 639 language codes, correctly identifying the language and automatically italicizing for you. Please use these templates rather than just manually italicizing non-English material. (See WP:Manual of Style/Accessibility § Other languages for more information.)
Template talk:Convert/Archive 3#Crore; Template talk:Convert/Archive 3#Lakh and crore; I have not yet examined the RfC at WT:Manual of Style/Dates and numbers#RfC Indian numbering conventions. The above discussions point out that lakh and crore are not units. They are like million which is also not a unit. However, if convert could do something ...
More commonly, question-answering systems can pull answers from an unstructured collection of natural language documents. Some examples of natural language document collections used for question answering systems include: a local [clarification needed] collection of reference texts; internal organization [ambiguous] documents and web pages