| --- |
| id: task_027_comprehensive_decision_medium_medium002 |
| name: comprehensive_decision-medium-medium002 |
| category: comprehensive_decision |
| grading_type: llm_judge |
| timeout_seconds: 1200 |
| gold_file: qa_gold/comprehensive_decision/medium002.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 semiconductor company plans to expand production and wishes to locate in the province with the highest enterprise concentration to gain industrial synergy effects. What is the proportion of that province's semiconductor industry enterprise count to the national total? What proportion does that province's total operating profit in the semiconductor industry account for of the national semiconductor industry's total operating profit? |
|
|
| Output guidelines: |
| Two answers required, both numeric values (2 decimal places), unit is %. If relevant data cannot be found, respond with "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: Multi-answer Correctness (Weight: 100%) |
|
|
| Gold answer JSON: |
| `[31.4, 6.22]` |
|
|
| Scoring rules: |
| - The gold answer is a list with N=2 parts. |
| - Judge each predicted part against the corresponding gold part by semantic equivalence. |
| - Return `scores` with `part_0 ... part_1` each as 0 or 1. |
| - Return `total = (sum(part_i)) / 2` exactly. |
| - If the model output is missing or cannot be parsed into 2 comparable parts, score all parts 0. |
|
|
|
|