| You are going to pretend to be Concept2PromptAI or C2P_AI for short. C2P_AI takes concepts and turns them into prompts for generative AIs that create images. | |
| You will ask the user for a concept then provide a prompt for it in a copyable code-box. | |
| After providing a prompt, ask if the User wants three different options for prompts for the concept or if they wish to move to a new concept. | |
| Use the following examples as a guide: | |
| Concept: A macro shot of a stempunk insect |
| ChatGPT, we're going to play a game. | |
| I'm going to give you a category, and a selection of subcategories, using this format: | |
| "Category"("subcategory")("subcategory") | |
| There may be zero subcategories, or more subcategories. To a response to each prompt, you should do a bulleted list of 20 items, working down on a scale in increments from 100% to 0%, getting further from matching the prompt the further down the list and further away from 100% it is. | |
| At 100%, you should put something that fits in the primary category and all the subcategories very well. Near the 50%, it should fit in the category, and roughly half of the subcatagory. At 0% it should match the category and no subcategory. |
| COUNTRY,CODE COUNTRY,SOURCE,CODE SOURCE,SOURCE_ID,SUBJECT,CODE SUBJECT,TYPE OF DATA,CODE TYPE OF DATA,WORKER COVERAGE,CODE WORKER COVERAGE,SEX,CODE SEX,TABLE,CODE TABLE,CLASSIFICATION,CODE CLASSIFICATION,SUB-CLASSIFICATION,CODE SUB-CLASSIFICATION,D1999,D2000,D2001,D2002,D2003,D2004,D2005,D2006,D2007,D2008,NOTES, | |
| "Austria","AT","Labour force survey","BA",,"Total employment","2E","Not used","2X","Total coverage","21","Total men and women","2A","Total employment, by occupation","2C","ISCO-88","O3","Total","00_",3762.3,3776.5,3799.6,3835.7,3798.4,3744,3823.5,3928.3,4027.9,4089.986,"Persons aged 15 years and over. Excluding conscripts on compulsory military service. 2004: Break. Prior to 2004: including conscripts. ", | |
| "Austria","AT","Labour force survey","BA",,"Total employment","2E","Not used","2X","Total coverage","21","Total men and women","2A","Total employment, by occupation","2C","ISCO-88","O3","1 Legislators, senior officials and managers","01_",276.5,276.9,293.8,274.2,283.7,243.3,286.2,279.4,286.7,281.576, |
| {"IDA07*IDPR2*IDTIME":{"label":" Occupati per Ateco 2007, Professione 2011 e Tempo e frequenza - Italia - 15 anni e pi\u00f9","value":[854.12,826.15,821.7,879.01,889.63,837.74,802.04,813.9,860.17,874.85,849.09,780.16,860.95,862.87,892.36,831.91,789.91,819.95,873.46,844.32,833.38,794.17,875.35,834.75,829.25,799.15,766.44,787.15,833.45,809.58,811.75,726.54,798.96,854.78,866.72,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,null,n |
| {"IDPR2":{"label":" Occupati per Professione 2011 - Italia - 15 anni e pi\u00f9 - 2014","value":[7641.59,588.6,3111.86,3941.13,6740.97,2541.95,4199.03,5226.19,3427.02,1799.16,2433.06,237.1,22278.92],"dimension":{"id":["IDPR2"],"size":[13],"IDPR2":{"label":"Professione 2011","category":{"index":{"1":0,"2":1,"3":2,"4":3,"5":4,"6":5,"7":6,"8":7,"9":8,"10":9,"11":10,"12":11,"13":12},"label":{"1":"qualificate e tecniche","2":"dirigenti e imprenditori","3":"professioni intellettuali","4":"professioni tecniche","5":"impiegati e addetti al commercio e servizi","6":"impiegati","7":"vendita e serv. personali","8":"operari e artigiani","9":"artigiani, operai specializzati, agricoltori","10":"conduttori di impianti","11":"personale non qualificato","12":"forze armate","13":"totale"}}}}}} |
The first goal to describe a little what would be call misperimenting with graphDB, RDF, and all fun stuff, without being to formal, and (I am very sorry for that) some misenglish everywhere.
And of course if it could help or inspire anyone for more useful tests it should be great (in did this a few month ago but have not time to pursue).
There are not so many graphDB implementations, it is quiet odd considering the hype of NoSql idea and current social graph applications.