tasks/task_038_comprehensive_decision_medium_medium013.md

metadata

id: task_038_comprehensive_decision_medium_medium013
name: comprehensive_decision-medium-medium013
category: comprehensive_decision
grading_type: llm_judge
timeout_seconds: 1200
gold_file: qa_gold/comprehensive_decision/medium013.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 scientific research and technical services enterprise wishes to identify the province with the fastest net profit growth in the industry to guide market expansion. What is the indicator value for the province with the highest median year-on-year net profit growth rate in the national scientific research and technical services industry? What is the nationwide rank of the enterprise with the highest such indicator in that province among all enterprises in this industry?

Output guidelines: Two answers required: first is a numeric value (2 decimal places, unit %), i.e. the indicator value for the province with the highest "median year-on-year net profit growth rate" in this industry nationwide; second is a rank number (integer, e.g. "23" means 23rd place), i.e. the nationwide rank of the enterprise with the highest "year-on-year net profit growth rate" in that province among all enterprises in this industry. 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: [13.81, 23]

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.