human
\nHere is the text extracted from a document using an OCR engine. \nThe text might have some transcription errors, and the order of the words might be wrong for some parts. \nYou are an annotator and your task is to generate 10 question/answer pairs based on the provided text. \nFocus on the parts that seem to have been well transcribed, and some of the questions need to be based on key/value pairs if it exists in the document. \nThe output should be a json dict, and answer need to contain only the correct value. Ensure that the output can be parsed using json.loads with python\n\nExtracted Text:\nACCESSING THE AUTOMATED REPORTING SYSTEM (ARS) 1 ₹ Double-Click on the "Automated Reporting System" subfolder. This will start the ARS application and a query window will appear. -0x Tiburon Menu Die Tiburon Inc. Tiburon Menu a Version 3.01 + Corrections System Copyright (c) 1998 Tiburon Inc., Fremont, CA Police System + C] ARS Maintenance Project Name: Milwauk El EN Automated Reporting System Automated Reporting System Product ID: 7.4.0 Il] Issue Supplements r12.01 Product Release: 10 DECEMBER 2004 14:52:17 Release Date: Bicycle El Crime Analysis Build Machine: TMCMULLEN3 # C Crime Watch t Criminal Records ] False Alarms Field Interview System # - Fleet Maintenance + Gang & Guns Registration & Incident + CI Inventory + 1 Juvenile & C License and Permits El Officer Activity t Pawned Property C t ] Service Requests + Special Flags + Special Intelligence & Traffic Management # 0 Warrants + Shared Subsystems 0 t Utilitie
gpt
--- Reasoning ---
1. Is the question multiple-choice question?
No
2. Is it implied multiple-choice question?
No
3. If two experts were independently asked the question, will the final answer be exactly the same?
No

--- Answer ---
open