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id: task_030_comprehensive_decision_medium_medium005
name: comprehensive_decision-medium-medium005
category: comprehensive_decision
grading_type: llm_judge
timeout_seconds: 1200
gold_file: qa_gold/comprehensive_decision/medium005.json
workspace_files: [
{
"source": "database/bilingual_translation_english_chinese.json",
"dest": "database/bilingual_translation_english_chinese.json"
},
{
"source": "database/enterprise/company_core.csv",
"dest": "database/enterprise/company_core.csv"
},
{
"source": "database/enterprise/company_operation_status.csv",
"dest": "database/enterprise/company_operation_status.csv"
},
{
"source": "database/enterprise/company_operation_status_detail.csv",
"dest": "database/enterprise/company_operation_status_detail.csv"
},
{
"source": "database/enterprise/company_operation_yearly_status.csv",
"dest": "database/enterprise/company_operation_yearly_status.csv"
},
{
"source": "database/enterprise/company_profile.csv",
"dest": "database/enterprise/company_profile.csv"
},
{
"source": "database/enterprise/company_profile_as.csv",
"dest": "database/enterprise/company_profile_as.csv"
},
{
"source": "database/enterprise/company_profile_eu.csv",
"dest": "database/enterprise/company_profile_eu.csv"
},
{
"source": "database/enterprise/company_profile_na.csv",
"dest": "database/enterprise/company_profile_na.csv"
},
{
"source": "database/enterprise/company_profile_oc.csv",
"dest": "database/enterprise/company_profile_oc.csv"
},
{
"source": "database/industry/national_industry_status.csv",
"dest": "database/industry/national_industry_status.csv"
},
{
"source": "database/industry/national_industry_status_detail.csv",
"dest": "database/industry/national_industry_status_detail.csv"
},
{
"source": "database/industry/national_industry_yearly_status.csv",
"dest": "database/industry/national_industry_yearly_status.csv"
},
{
"source": "database/industry/regional_industry_status.csv",
"dest": "database/industry/regional_industry_status.csv"
},
{
"source": "database/industry/regional_industry_status_detail.csv",
"dest": "database/industry/regional_industry_status_detail.csv"
},
{
"source": "database/industry/regional_industry_yearly_status.csv",
"dest": "database/industry/regional_industry_yearly_status.csv"
},
{
"source": "database/internal_metrics.csv",
"dest": "database/internal_metrics.csv"
},
{
"source": "database/policy/policy_release_status.csv",
"dest": "database/policy/policy_release_status.csv"
},
{
"source": "database/policy/policy_resource.csv",
"dest": "database/policy/policy_resource.csv"
}
]
---
## Prompt
In 2022, from all private enterprises in the food and beverage industry, aggregate government rewards and subsidy amounts by province of registration to find the province with the highest provincial subsidy total. How many hundred million yuan in government subsidies did private enterprises in that province receive in total?
Output guidelines:
The answer should be a numerical value (2 decimal places), unit is hundred million yuan. If relevant data cannot be found, please answer "No relevant data found"
Only use files under `./database/`.
## Expected Behavior
Agent should read the provided `database/` files, compute the result, and return the final answer. The final answer must follow the required output format.
## Grading Criteria
- [ ] Final answer semantically matches the gold `answer`.
- [ ] Output format follows `guidelines`.
## LLM Judge Rubric
### Criterion 1: Single-answer Correctness (Weight: 100%)
Gold answer JSON:
`12.6`
Scoring rules:
- Judge semantic equivalence between the model final answer and the gold answer.
- Return `scores` with one key `match` as 1 or 0.
- Return `total` as 1.0 if equivalent, otherwise 0.0.
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