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{
"cells": [
{
"cell_type": "code",
"execution_count": 60,
"id": "49140416",
"metadata": {},
"outputs": [],
"source": [
"import os,re\n",
"import pandas as pd\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "621c0c37",
"metadata": {},
"outputs": [],
"source": [
"prompts = pd.read_csv('shortprompts.csv')"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "27cf3f0e",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 51,
"id": "bc14f4b1",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 78,
"id": "5f2cb0c9",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 80,
"id": "f5e935fa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['wife',\n",
" 'construction worker',\n",
" 'hostess',\n",
" 'aerospace engineer',\n",
" 'manicurist',\n",
" 'designer',\n",
" 'financial advisor',\n",
" 'bus driver',\n",
" 'financial analyst',\n",
" 'butcher',\n",
" 'cook',\n",
" 'medical records specialist',\n",
" 'baker',\n",
" 'nursing assistant',\n",
" 'machinist',\n",
" 'uncle',\n",
" 'interviewer',\n",
" 'truck driver',\n",
" 'supervisor',\n",
" 'computer programmer',\n",
" 'boyfriend',\n",
" 'language pathologist',\n",
" 'security guard',\n",
" 'computer support specialist',\n",
" 'paralegal',\n",
" 'spouse',\n",
" 'data entry keyer',\n",
" 'wholesale buyer',\n",
" 'accountant',\n",
" 'stepmom',\n",
" 'dental assistant',\n",
" 'sister',\n",
" 'insurance agent',\n",
" 'logistician',\n",
" 'partner',\n",
" 'fitness instructor',\n",
" 'welder',\n",
" 'grandpa',\n",
" 'painter',\n",
" 'financial manager',\n",
" 'carpet installer',\n",
" 'physical therapist',\n",
" 'market research analyst',\n",
" 'ceo',\n",
" 'singer',\n",
" 'teller',\n",
" 'stepsister',\n",
" 'coach',\n",
" 'receptionist',\n",
" 'compliance officer',\n",
" 'taxi driver',\n",
" 'father-in-law',\n",
" 'dental hygienist',\n",
" 'maid',\n",
" 'janitor',\n",
" 'roofer',\n",
" 'stepdad',\n",
" 'best friend',\n",
" 'father',\n",
" 'sibling',\n",
" 'husband',\n",
" 'lawyer',\n",
" 'occupational therapist',\n",
" 'head cook',\n",
" 'dispatcher',\n",
" 'employer',\n",
" 'cousin',\n",
" 'office worker',\n",
" 'graphic designer',\n",
" 'girlfriend',\n",
" 'mechanical engineer',\n",
" 'marketing manager',\n",
" 'health technician',\n",
" 'mother',\n",
" 'grandmother',\n",
" 'plumber',\n",
" 'colleague',\n",
" 'cleaner',\n",
" 'mover',\n",
" 'correctional officer',\n",
" 'stocker',\n",
" 'underwriter',\n",
" 'teaching assistant',\n",
" 'radiologic technician',\n",
" 'manager',\n",
" 'teacher',\n",
" 'bartender',\n",
" 'payroll clerk',\n",
" 'civil engineer',\n",
" 'customer service representative',\n",
" 'stepfather',\n",
" 'electrician',\n",
" 'architect',\n",
" 'therapist',\n",
" 'pharmacy technician',\n",
" 'tutor',\n",
" 'producer',\n",
" 'repair worker',\n",
" 'stepmother',\n",
" 'executive assistant',\n",
" 'groundskeeper',\n",
" 'firefighter',\n",
" 'sales manager',\n",
" 'air conditioning installer',\n",
" 'cashier',\n",
" 'neighbor',\n",
" 'dentist',\n",
" 'scientist',\n",
" 'engineer',\n",
" 'childcare worker',\n",
" 'police officer',\n",
" 'mother-in-law',\n",
" 'industrial engineer',\n",
" 'clergy',\n",
" 'parent',\n",
" 'niece',\n",
" 'office clerk',\n",
" 'stepbrother',\n",
" 'metal worker',\n",
" 'writer',\n",
" 'farmer',\n",
" 'nurse',\n",
" 'musician',\n",
" 'public relations specialist',\n",
" 'host',\n",
" 'carpenter',\n",
" 'career counselor',\n",
" 'jailer',\n",
" 'grandfather',\n",
" 'librarian',\n",
" 'network administrator',\n",
" 'social assistant',\n",
" 'credit counselor',\n",
" 'pharmacist',\n",
" 'employee',\n",
" 'hairdresser',\n",
" 'nephew',\n",
" 'printing press operator',\n",
" 'tractor operator',\n",
" 'artist',\n",
" 'dishwasher',\n",
" 'director',\n",
" 'postal worker',\n",
" 'drywall installer',\n",
" 'author',\n",
" 'interior designer',\n",
" 'grandma',\n",
" 'pilot',\n",
" 'aunt',\n",
" 'claims appraiser',\n",
" 'plane mechanic',\n",
" 'fast food worker',\n",
" 'machinery mechanic',\n",
" 'school bus driver',\n",
" 'mechanic',\n",
" 'photographers',\n",
" 'son',\n",
" 'inventory clerk',\n",
" 'detective',\n",
" 'mental health counselor',\n",
" 'software developer',\n",
" 'it specialist',\n",
" 'brother',\n",
" 'real estate broker',\n",
" 'courier',\n",
" 'veterinarian',\n",
" 'aide',\n",
" 'clerk',\n",
" 'psychologist',\n",
" 'computer systems analyst',\n",
" 'community manager',\n",
" 'file clerk',\n",
" 'massage therapist',\n",
" 'daughter',\n",
" 'sheet metal worker',\n",
" 'purchasing agent',\n",
" 'laboratory technician',\n",
" 'waiter',\n",
" 'dad',\n",
" 'friend',\n",
" 'facilities manager',\n",
" 'waitress',\n",
" 'doctor',\n",
" 'social worker',\n",
" 'salesperson',\n",
" 'mom',\n",
" 'electrical engineer']"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "code",
"execution_count": 45,
"id": "fc67b38a",
"metadata": {},
"outputs": [],
"source": [
"adjectives = prompts['Descriptive-Adj'].tolist()[:10]\n",
"professions = [p.lower() for p in prompts['Occupation-Noun'].tolist()]"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.12"
}
},
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}
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