tasks/task_011_comprehensive_decision_hard_hard005.md

metadata

id: task_011_comprehensive_decision_hard_hard005
name: comprehensive_decision-hard-hard005
category: comprehensive_decision
grading_type: llm_judge
timeout_seconds: 1200
gold_file: qa_gold/comprehensive_decision/hard005.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, for the information transmission, software and information technology services industry, an industry research institute sought to obtain a policy-adjusted comprehensive innovation efficiency indicator by superimposing the incentive effect of local policy support on top of raw innovation efficiency. The calculation logic is as follows: first, exclude from enterprise microdata any samples with missing R&D expenditure or annual domestic invention patent grants; for the remaining valid enterprises, aggregate by province and calculate the ratio of total invention patent grants to total R&D expenditure (converted to 100 million yuan) for each province as the province's raw innovation efficiency benchmark; then use the proportion of policy items in that province out of all information technology policies as the policy support coefficient, and multiply the raw efficiency benchmark by (1 plus the policy support coefficient) to obtain the final policy-adjusted innovation efficiency. Among all provinces with data, what is the specific value of the province with the highest adjusted efficiency?

Output guidelines: The answer should be a numerical value with 2 decimal places. 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: 63.74

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.