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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.
Citations may or may not appear in a plot summary. The work of fiction itself is the primary source, and doesn't usually need to be cited for simple plot details. Secondary sources are needed for commentary, but that generally shouldn't appear in a plot summary. Citations are appropriate when including notable quotes from the work.
To maintain readability, plot summaries should have just enough detail to give readers an understanding of the work. Occasionally, you'll find excessively detailed plot summaries that overwhelm readers with a summary of every scene. In this case, it's frequently best to rewrite the plot summary from scratch.
Storyland is a browser-based narrative work of electronic literature.The project is included in the first Electronic Literature Collection. [1] It was created by Nanette Wylde in 2000 and is considered a form of Combinatory Narrative or Generative Poetry which is created with the use of the computer's random function.
A plot summary is a retelling, a summary, or an abridged or shortened précis of the events that occur within a work of fiction. The purpose of a plot summary is to help the reader understand the important events within a work of fiction, be they of the work as a whole or of an individual character.
"Henry James, This One’s For You" is a 2005 science fiction short story by American writer Jack McDevitt. It was a finalist for the 2006 Nebula Award for Best Short Story . Plot summary
The story began on Jan. 14, 2009, when Calusinski, then 22, was working as a teacher's assistant at the Minee Subee day care in Lincolnshire, a suburb of Chicago. Late that afternoon, Calusinski ...
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.
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