Upload fact_check_report.py with huggingface_hub
Browse files- fact_check_report.py +252 -0
fact_check_report.py
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| 1 |
+
#!/usr/bin/env python3
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| 2 |
+
"""
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| 3 |
+
FACT-CHECK REPORT: Training Data Verification
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| 4 |
+
Checking all facts in training.csv for accuracy
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| 5 |
+
"""
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| 6 |
+
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| 7 |
+
def fact_check_training_data():
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| 8 |
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"""
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| 9 |
+
Comprehensive fact-check of all data in training.csv
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| 10 |
+
β
= Correct, β οΈ = Needs correction, β = Incorrect
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| 11 |
+
"""
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| 12 |
+
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| 13 |
+
print("π FACT-CHECK REPORT: Training Data Verification")
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| 14 |
+
print("=" * 60)
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| 15 |
+
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| 16 |
+
fact_checks = [
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| 17 |
+
# PARIS DATA
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| 18 |
+
{
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| 19 |
+
'topic': 'Paris Population',
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| 20 |
+
'claim': 'Paris population 2.1 million',
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| 21 |
+
'status': 'β οΈ',
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| 22 |
+
'correct_fact': 'Paris city: ~2.16M (2023), Metro area: ~12.27M',
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| 23 |
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'note': 'Close enough - depends on city vs metro definition'
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| 24 |
+
},
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| 25 |
+
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| 26 |
+
# MOUNT EVEREST DATA
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| 27 |
+
{
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| 28 |
+
'topic': 'Mount Everest Height',
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| 29 |
+
'claim': '29,032 feet tall',
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| 30 |
+
'status': 'β
',
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| 31 |
+
'correct_fact': '29,031.7 feet (8,848.86 meters) - 2020 official measurement',
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| 32 |
+
'note': 'Essentially correct (rounded)'
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| 33 |
+
},
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| 34 |
+
{
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| 35 |
+
'topic': 'Mount Everest Location',
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| 36 |
+
'claim': 'Located in Nepal and Tibet',
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| 37 |
+
'status': 'β
',
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| 38 |
+
'correct_fact': 'Nepal-Tibet (China) border - summit on border',
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| 39 |
+
'note': 'Correct'
|
| 40 |
+
},
|
| 41 |
+
|
| 42 |
+
# EINSTEIN DATA
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| 43 |
+
{
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| 44 |
+
'topic': 'Einstein Birth Year',
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| 45 |
+
'claim': 'Born 1879',
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| 46 |
+
'status': 'β
',
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| 47 |
+
'correct_fact': 'Born March 14, 1879',
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| 48 |
+
'note': 'Correct'
|
| 49 |
+
},
|
| 50 |
+
{
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| 51 |
+
'topic': 'Einstein Theory',
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| 52 |
+
'claim': 'Developed theory of relativity',
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| 53 |
+
'status': 'β
',
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| 54 |
+
'correct_fact': 'Special (1905) and General (1915) Relativity',
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| 55 |
+
'note': 'Correct'
|
| 56 |
+
},
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| 57 |
+
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| 58 |
+
# GREAT WALL DATA
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| 59 |
+
{
|
| 60 |
+
'topic': 'Great Wall Length',
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| 61 |
+
'claim': '13,000 miles long',
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| 62 |
+
'status': 'β
',
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| 63 |
+
'correct_fact': '13,170+ miles (21,196+ km) including branches',
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| 64 |
+
'note': 'Correct (total with all sections)'
|
| 65 |
+
},
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| 66 |
+
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| 67 |
+
# SHAKESPEARE DATA
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| 68 |
+
{
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| 69 |
+
'topic': 'Shakespeare Plays Count',
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| 70 |
+
'claim': 'Wrote 39 plays',
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| 71 |
+
'status': 'β
',
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| 72 |
+
'correct_fact': '37-39 plays (scholars debate attribution)',
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| 73 |
+
'note': 'Correct range'
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| 74 |
+
},
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| 75 |
+
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| 76 |
+
# AMAZON RIVER DATA
|
| 77 |
+
{
|
| 78 |
+
'topic': 'Amazon River Length',
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| 79 |
+
'claim': '4,000 miles long',
|
| 80 |
+
'status': 'β
',
|
| 81 |
+
'correct_fact': '~4,000 miles (6,400 km)',
|
| 82 |
+
'note': 'Correct'
|
| 83 |
+
},
|
| 84 |
+
|
| 85 |
+
# WORLD WAR II DATA
|
| 86 |
+
{
|
| 87 |
+
'topic': 'WWII Duration',
|
| 88 |
+
'claim': '1939 to 1945, 6 years total',
|
| 89 |
+
'status': 'β
',
|
| 90 |
+
'correct_fact': 'Sept 1, 1939 - Sept 2, 1945 (6 years)',
|
| 91 |
+
'note': 'Correct'
|
| 92 |
+
},
|
| 93 |
+
|
| 94 |
+
# SUN DATA
|
| 95 |
+
{
|
| 96 |
+
'topic': 'Sun Distance',
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| 97 |
+
'claim': '93 million miles from Earth',
|
| 98 |
+
'status': 'β
',
|
| 99 |
+
'correct_fact': '92.96 million miles (149.6 million km) average',
|
| 100 |
+
'note': 'Correct (1 AU)'
|
| 101 |
+
},
|
| 102 |
+
{
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| 103 |
+
'topic': 'Sun Fuel',
|
| 104 |
+
'claim': 'Burns hydrogen',
|
| 105 |
+
'status': 'β
',
|
| 106 |
+
'correct_fact': 'Nuclear fusion: hydrogen β helium',
|
| 107 |
+
'note': 'Correct (hydrogen fusion)'
|
| 108 |
+
},
|
| 109 |
+
|
| 110 |
+
# BASKETBALL DATA
|
| 111 |
+
{
|
| 112 |
+
'topic': 'Basketball Players',
|
| 113 |
+
'claim': '5 players per team',
|
| 114 |
+
'status': 'β
',
|
| 115 |
+
'correct_fact': '5 players on court per team',
|
| 116 |
+
'note': 'Correct'
|
| 117 |
+
},
|
| 118 |
+
{
|
| 119 |
+
'topic': 'Basketball Game Length',
|
| 120 |
+
'claim': 'Games last 48 minutes',
|
| 121 |
+
'status': 'β
',
|
| 122 |
+
'correct_fact': 'NBA: 48 min (4Γ12min), FIBA: 40 min (4Γ10min)',
|
| 123 |
+
'note': 'Correct for NBA'
|
| 124 |
+
},
|
| 125 |
+
|
| 126 |
+
# TITANIC DATA
|
| 127 |
+
{
|
| 128 |
+
'topic': 'Titanic Sinking',
|
| 129 |
+
'claim': 'Sank in 1912, hit an iceberg',
|
| 130 |
+
'status': 'β
',
|
| 131 |
+
'correct_fact': 'April 15, 1912, hit iceberg',
|
| 132 |
+
'note': 'Correct'
|
| 133 |
+
},
|
| 134 |
+
|
| 135 |
+
# OXYGEN DATA
|
| 136 |
+
{
|
| 137 |
+
'topic': 'Oxygen Symbol',
|
| 138 |
+
'claim': 'Chemical symbol O',
|
| 139 |
+
'status': 'β
',
|
| 140 |
+
'correct_fact': 'O (single atom), Oβ (molecular oxygen)',
|
| 141 |
+
'note': 'Correct - O is atomic symbol'
|
| 142 |
+
},
|
| 143 |
+
{
|
| 144 |
+
'topic': 'Oxygen Atomic Number',
|
| 145 |
+
'claim': 'Atomic number 8',
|
| 146 |
+
'status': 'β
',
|
| 147 |
+
'correct_fact': 'Atomic number 8',
|
| 148 |
+
'note': 'Correct'
|
| 149 |
+
},
|
| 150 |
+
|
| 151 |
+
# PIZZA DATA
|
| 152 |
+
{
|
| 153 |
+
'topic': 'Pizza Origin',
|
| 154 |
+
'claim': 'Originated in Italy',
|
| 155 |
+
'status': 'β
',
|
| 156 |
+
'correct_fact': 'Modern pizza: Naples, Italy (18th-19th century)',
|
| 157 |
+
'note': 'Correct'
|
| 158 |
+
},
|
| 159 |
+
|
| 160 |
+
# DOG DATA
|
| 161 |
+
{
|
| 162 |
+
'topic': 'Dog Lifespan',
|
| 163 |
+
'claim': 'Average lifespan 10-13 years',
|
| 164 |
+
'status': 'β
',
|
| 165 |
+
'correct_fact': '10-13 years average (varies by breed)',
|
| 166 |
+
'note': 'Correct'
|
| 167 |
+
},
|
| 168 |
+
|
| 169 |
+
# MOON DATA
|
| 170 |
+
{
|
| 171 |
+
'topic': 'Moon Distance',
|
| 172 |
+
'claim': '238,900 miles from Earth',
|
| 173 |
+
'status': 'β
',
|
| 174 |
+
'correct_fact': '238,855 miles (384,400 km) average',
|
| 175 |
+
'note': 'Very close (rounded)'
|
| 176 |
+
},
|
| 177 |
+
{
|
| 178 |
+
'topic': 'Moon Orbit',
|
| 179 |
+
'claim': 'Takes 27 days to orbit',
|
| 180 |
+
'status': 'β
',
|
| 181 |
+
'correct_fact': '27.3 days (sidereal period)',
|
| 182 |
+
'note': 'Correct (rounded)'
|
| 183 |
+
},
|
| 184 |
+
|
| 185 |
+
# COFFEE DATA
|
| 186 |
+
{
|
| 187 |
+
'topic': 'Coffee Origin',
|
| 188 |
+
'claim': 'Originated in Ethiopia',
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| 189 |
+
'status': 'β
',
|
| 190 |
+
'correct_fact': 'Ethiopia (coffee plant native there)',
|
| 191 |
+
'note': 'Correct'
|
| 192 |
+
},
|
| 193 |
+
|
| 194 |
+
# PENGUIN DATA
|
| 195 |
+
{
|
| 196 |
+
'topic': 'Penguin Flight',
|
| 197 |
+
'claim': 'Flightless birds',
|
| 198 |
+
'status': 'β
',
|
| 199 |
+
'correct_fact': 'Flightless birds (can "fly" underwater)',
|
| 200 |
+
'note': 'Correct'
|
| 201 |
+
},
|
| 202 |
+
{
|
| 203 |
+
'topic': 'Penguin Habitat',
|
| 204 |
+
'claim': 'Live in Antarctica',
|
| 205 |
+
'status': 'β οΈ',
|
| 206 |
+
'correct_fact': 'Some live in Antarctica, others in South America, Africa, Australia',
|
| 207 |
+
'note': 'Oversimplified - many species live elsewhere'
|
| 208 |
+
},
|
| 209 |
+
|
| 210 |
+
# HEART DATA
|
| 211 |
+
{
|
| 212 |
+
'topic': 'Human Heart Chambers',
|
| 213 |
+
'claim': 'Has 4 chambers',
|
| 214 |
+
'status': 'β
',
|
| 215 |
+
'correct_fact': '4 chambers: 2 atria, 2 ventricles',
|
| 216 |
+
'note': 'Correct'
|
| 217 |
+
}
|
| 218 |
+
]
|
| 219 |
+
|
| 220 |
+
print(f"π CHECKING {len(fact_checks)} FACTS FROM TRAINING DATA:\n")
|
| 221 |
+
|
| 222 |
+
correct_count = 0
|
| 223 |
+
warning_count = 0
|
| 224 |
+
|
| 225 |
+
for check in fact_checks:
|
| 226 |
+
print(f"{check['status']} {check['topic']}")
|
| 227 |
+
print(f" Claim: {check['claim']}")
|
| 228 |
+
print(f" Fact: {check['correct_fact']}")
|
| 229 |
+
print(f" Note: {check['note']}")
|
| 230 |
+
print()
|
| 231 |
+
|
| 232 |
+
if check['status'] == 'β
':
|
| 233 |
+
correct_count += 1
|
| 234 |
+
elif check['status'] == 'β οΈ':
|
| 235 |
+
warning_count += 1
|
| 236 |
+
|
| 237 |
+
print("=" * 60)
|
| 238 |
+
print(f"π FACT-CHECK SUMMARY:")
|
| 239 |
+
print(f"β
Correct: {correct_count}")
|
| 240 |
+
print(f"β οΈ Minor issues: {warning_count}")
|
| 241 |
+
print(f"β Incorrect: 0")
|
| 242 |
+
print(f"π Accuracy: {(correct_count / len(fact_checks)) * 100:.1f}%")
|
| 243 |
+
|
| 244 |
+
print(f"\nπ― RECOMMENDATIONS:")
|
| 245 |
+
print(f"1. β οΈ Clarify penguin habitat: 'Some penguins live in Antarctica'")
|
| 246 |
+
print(f"2. β
All other facts are accurate")
|
| 247 |
+
print(f"3. β
Your training data is very high quality!")
|
| 248 |
+
|
| 249 |
+
return fact_checks
|
| 250 |
+
|
| 251 |
+
if __name__ == "__main__":
|
| 252 |
+
fact_check_training_data()
|