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A plot summary is not a recap. It should not cover every scene or every moment of a story. A summary is not meant to reproduce the experience of reading or watching the work. In fact, readers might be here because they didn't understand the original. Just repeating what they have already seen or read is unlikely to help them.
On Wikipedia, editors are not required to use secondary sources for plot summaries per MOS:PLOTSOURCE; the reasoning goes that it is generally assumed that the work itself is the primary source for the plot summary. However, relying on this can lead to original research and overly long summaries. Sourcing plot summaries provides clear benefits ...
For tagging articles that have overly long plot summaries. Template parameters [Edit template data] This template prefers inline formatting of parameters. Parameter Description Type Status Scope (e.g. section) 1 This parameter allows an editor to replace the default word "article" with another word, usually "section" or "paragraph" Content optional Plural? plural Set to 'yes' if the article ...
The coverage of a fictional work should not be a mere plot summary. A summary should facilitate substantial coverage of the work's real-world development, reception, and significance. This means that an article about a work of fiction or elements from such works should not solely be a summary of the primary and tertiary sources , they should ...
A concise plot summary is appropriate as part of the larger coverage of a fictional work." Indicate this in the lead section and use it a springboard into writing exactly how we can ensure that plot summaries are concise. Another reference to make is WP:OR, specifically, WP:PSTS. Fictional works are primary sources, so we can only make ...
A story generator or plot generator is a tool that generates basic narratives or plot ideas. The generator could be in the form of a computer program, a chart with multiple columns, a book composed of panels that flip independently of one another, or a set of several adjacent reels that spin independently of one another, allowing a user to select elements of a narrative plot.
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Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.