Task task5_dedup_contact

# Contact List Deduplicator

You have a CSV file `input/contacts.csv` containing contact information with potential duplicates.

Your task is to identify and merge duplicate contacts based on matching criteria, then generate a JSON report.

## Duplicate Detection Rules

Two contacts are duplicates if ANY of the following match:
1. **Phone numbers match** (after normalization - remove spaces, dashes, parentheses)
2. **Email addresses match** (case-insensitive)
3. **Names are very similar** (exact match ignoring case, or initials match with same last name)

## Requirements

1. Read `input/contacts.csv`
2. Identify all duplicate contacts
3. Generate `input/deduped.json` with this exact structure:

```json
{
"original_count": 100,
"unique_count": 85,
"duplicates_found": 15,
"duplicate_groups": [
{
"primary": {
"name": "John Smith",
"email": "[email protected]",
"phone": "555-1234",
"company": "Acme Corp"
},
"duplicates": [
{
"name": "J. Smith",
"email": "[email protected]",
"phone": "555-1234",
"company": "Acme Corp"
}
],
"match_reason": "phone"
}
]
}
```

## Important Notes

- The primary contact should be the one with the most complete information (fewest empty fields)
- Normalize phone numbers before comparison: remove all spaces, dashes, and parentheses
- Email matching should be case-insensitive
- Match reasons can be: "phone", "email", "name", or combinations like "phone_and_email"
- Each duplicate group should list the primary contact and all its duplicates
- Original count includes all contacts, unique count is after deduplication
- Duplicates found is the number of duplicate entries (not the number of groups)

PS: You are currently working in an automated system and cannot ask any question or have back and forth with an user.

Results

24
Models Tested
33.3%
Success Rate
2m 30s
Avg Duration
15s - 10m 0s
Duration Range

Details

Score Model Duration Session (KB) test_1_file_exists.sh test_2_json_structure.sh test_3_counts.sh test_4_duplicate_detection.sh
100.0% litellm/DeepSeek-V3.2-sandbox 4m 27s 127.8
100.0% openrouter/google/gemini-3-pro-preview 2m 56s 74.6
100.0% openrouter/openai/gpt-5-nano 3m 1s 262.3
100.0% openrouter/anthropic/claude-opus-4.5 1m 30s 56.9
100.0% openrouter/qwen/qwen3-coder 3m 26s 197.7
100.0% openrouter/anthropic/claude-haiku-4.5 59s 56.0
100.0% openrouter/anthropic/claude-sonnet-4.5 1m 24s 52.9
100.0% openrouter/openai/gpt-4.1-mini 1m 49s 132.8
75.0% litellm/GLM-4.5-Air-FP8-dev 2m 27s 126.1
50.0% openrouter/openai/gpt-4o-mini 1m 41s 92.0
50.0% openrouter/deepseek/deepseek-v3.1-terminus 1m 54s 51.0
0.0% openrouter/google/gemini-2.5-flash-preview-09-2025 15s 18.4
0.0% openrouter/openai/gpt-5 3m 43s 287.8
0.0% openrouter/openai/gpt-oss-120b 34s 17.4
0.0% openrouter/x-ai/grok-3-mini 2m 12s 562.6
0.0% openrouter/google/gemini-2.5-pro 1m 26s 48.6
0.0% openrouter/google/gemini-2.5-flash-lite-preview-09-2025 41s 30.2
0.0% openrouter/openai/gpt-oss-20b 40s 61.6
0.0% openrouter/openai/gpt-5.2 1m 37s 148.4
0.0% openrouter/deepseek/deepseek-chat-v3-0324 1m 15s 125.5
0.0% litellm/GLM-4.6-trtllm-sandbox 10m 0s 0.0
0.0% openrouter/openai/gpt-4.1-nano 19s 45.8
0.0% openrouter/x-ai/grok-code-fast-1 1m 48s 124.1
0.0% openrouter/openai/gpt-5-mini 10m 0s 0.0