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Make Shift #93
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Congratulations! (I made a bot of Grenville Kleiser's Fifteen Thousand Useful Phrases |
It seems to call out for that, doesn't it? The ever-uncertain plausibility of the word "useful" in the title does a lot to make its idiosyncrasies especially fun. He must have been quite a character. |
Repository, text, and pdf.
This work arranges sentences and phrases from historical sources, making use of sentence similarity calculations based on word embeddings provided by the SpaCy NLP library in Python.
To scaffold a book-length structure, I turned to a site called TVMaze and drew on their API to extract sentences describing episodes of a reality TV show called The Apprentice. To build up some contrast, balance, and historical depth, I extracted sentences from the platform of the U.S. Republican Party during presidential election years during its first two decades. I also included sentences from an edition of Russell Conwell's "Acres of Diamonds" speech.
Finally, a certain poetic suggestiveness comes from drawing on Grenville Kleiser's century-old Fifteen Thousand Useful Phrases, which I stumbled across in a used bookstore. (It's engaging enough in its quirkiness that LibriVox readers have read the whole thing aloud.)
To put all this together, I used SpaCy's existing English-language word embedding model to compare sentence similarity. I took the sentences summarizing the TV episodes in their original order. Each sentence generates a two-paragraph block by drawing on the other sources.
It was interesting to experiment with paragraph-level structures and try to get some sense of continuity in variety that might work at larger scales.
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