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id: task_014_comprehensive_decision_hard_hard008
name: comprehensive_decision-hard-hard008
category: comprehensive_decision
grading_type: llm_judge
timeout_seconds: 1200
gold_file: qa_gold/comprehensive_decision/hard008.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, a private equity institution sought to identify high-quality provinces in the electricity, heat, gas and water production and supply industry that combine growth potential, market undervaluation, and innovation resilience. The screening logic has three layers: The first layer requires that the median year-over-year change in operating revenue of enterprises within the province be positive (>0%), to exclude regions where revenue is already shrinking; The second layer, based on the first layer results, further requires that the province's market valuation level be relatively low, i.e., the P/S ratio of all enterprises in the province must be lower than the median P/S ratio across all provinces nationwide (national median is calculated from the provincial P/S ratio series); The third layer adds an innovation requirement, i.e., the mean R&D investment ratio of enterprises in the province must be higher than the mean of all enterprises in the industry with R&D investment ratio records. How many provinces satisfy all three conditions simultaneously?
Output guidelines:
The answer should be an integer. Output only the number, without units or text. 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:
`4`
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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