id stringlengths 7 9 | question stringlengths 101 1.4k | guidelines stringlengths 108 498 | answer stringlengths 1 1.11k | metadata dict | steps listlengths 2 8 | steps_num int64 2 8 | milestone stringlengths 35 943 |
|---|---|---|---|---|---|---|---|
easy001 | In which province is the enterprise with the highest R&D investment ratio nationwide in 2022 located? | The answer must be "yes" or "no". Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | Jiangsu Province | {
"db": "bm_rag_qa",
"level": "easy",
"category": "comprehensive_decision"
} | [
"Filter all records with year=2022 from company_operation_status.csv, and extract the enterprise name and R&D investment ratio fields.",
"Filter enterprise records with non-null R&D investment ratio, sort by R&D investment ratio in descending order, and identify the enterprise with the highest R&D investment rati... | 3 | {"Enterprise with highest R&D investment ratio": "Yaoshi Shenkang Medical Equipment Company", "R&D investment ratio (%)": 934642.8, "Province of location": "Jiangsu Province"} |
easy002 | In 2022, nationwide, how is the chemical raw materials and chemical products manufacturing industry ranked by asset scale? Please list the top five provinces. | Answer format: [Province A, Province B, ...]. Output only province names, do not add any other explanatory text. If relevant data cannot be found, please answer "No relevant data found" | ["Shandong Province", "Zhejiang Province", "Jiangsu Province", "Shanghai", "Guangdong Province"] | {
"db": "bm_rag_qa",
"level": "easy",
"category": "comprehensive_decision"
} | [
"Filter all records with industry=\"Chemical Raw Materials and Chemical Products Manufacturing\" from regional_industry_status.csv, and extract the province and total assets fields.",
"Sort all provincial data by total assets in descending order to determine the asset scale ranking of each province. Extract the t... | 2 | {"Total assets in Shandong Province (yuan)": 544109686731.85, "Total assets in Zhejiang Province (yuan)": 401644798867.8, "Total assets in Jiangsu Province (yuan)": 250743006622.33, "Total assets in Shanghai (yuan)": 230472528900.23, "Total assets in Guangdong Province (yuan)": 176926240169.03, "Top five provinces": ["... |
easy003 | In 2022, in the Qilu region (Shandong Province), how many policies support Zhongbai Jinmao Chain Company in its industry? | The answer must be an exact number. Output only the number, do not add units, commas, or any textual explanation. If relevant data cannot be found, please answer "No relevant data found" | 2 | {
"db": "bm_rag_qa",
"level": "easy",
"category": "comprehensive_decision"
} | [
"Search for records of \"Zhongbai Jinmao Chain Company\" in company_profile.csv, extract the industry field, and determine that its industry is \"Wholesale and Retail Trade\".",
"Filter from policy_release_status.csv for all policy records with province=\"Shandong Province\", and policies where the industry field... | 3 | {"Industry of Zhongbai Jinmao Chain Company": "Wholesale and Retail Trade", "Shandong Province Local Policy - Shandong Provincial People's Government General Office Policy Count": 1, "Shandong Province Local Policy - Shandong Provincial Development and Reform Commission Policy Count": 1, "Number of policies in Shandong... |
easy004 | In 2022, nationwide, what is the ranking of provinces by asset size in the Information Transmission, Software and Information Technology Services industry? Please list the top five provinces. | Answer format: [Province A, Province B, ...]. Output only the province ranking, do not add any other explanatory text. If relevant data cannot be found, please answer "No relevant data found" | ["Beijing", "Zhejiang Province", "Guangdong Province", "Shanghai", "Jiangsu Province"] | {
"db": "bm_rag_qa",
"level": "easy",
"category": "comprehensive_decision"
} | [
"Filter from regional_industry_status.csv all records with industry=\"Information Transmission, Software and Information Technology Services\", and extract the province and total assets fields.",
"Sort all provincial data in descending order by total assets to determine the asset size ranking of each province. Ex... | 2 | {"Total assets of Beijing (CNY)": 10297490896006.5, "Total assets of Zhejiang Province (CNY)": 4115693929492.25, "Total assets of Guangdong Province (CNY)": 2262247330030.01, "Total assets of Shanghai (CNY)": 1282711003966.55, "Total assets of Jiangsu Province (CNY)": 177568006242.47, "Top five provinces by ranking": [... |
easy005 | In 2022, nationwide, what is the ranking of provinces by profitability in the Real Estate industry? Please list the top five provinces. | Answer format: [Province A, Province B, ...]. Output only the province ranking, do not add any other explanatory text. If relevant data cannot be found, please answer "No relevant data found" | ["Hong Kong SAR", "Guangdong Province", "Zhejiang Province", "Beijing", "Jilin Province"] | {
"db": "bm_rag_qa",
"level": "easy",
"category": "comprehensive_decision"
} | [
"Filter from regional_industry_status.csv all records with industry=\"Real Estate\", extract province and total net profit amount fields, finding data for 34 provinces/regions in the Real Estate industry.",
"Filter province records where total net profit amount is not null, totaling 34 valid records. Sort all pro... | 3 | {"Total net profit amount of Hong Kong SAR (CNY)": 86497465420.52, "Total net profit amount of Guangdong Province (CNY)": 70559018502.22, "Total net profit amount of Zhejiang Province (CNY)": 12297928184.06, "Total net profit amount of Beijing (CNY)": 8975618268.55, "Total net profit amount of Jilin Province (CNY)": 67... |
easy006 | In 2022, what is Sichuan Province's national ranking by average R&D investment in the Information Transmission, Software and Information Technology Services industry? | The answer must be an exact number representing the ranking. Output only the number, do not add units, commas, or any textual explanation. If relevant data cannot be found, please answer "No relevant data found" | 10 | {
"db": "bm_rag_qa",
"level": "easy",
"category": "comprehensive_decision"
} | [
"Filter from regional_industry_status.csv all records with industry=\"Information Transmission, Software and Information Technology Services\", finding data for 34 provinces/regions.",
"Extract the \"mean R&D investment amount\" field for each province to obtain mean R&D investment data for all provinces. Sort al... | 3 | {"Mean R&D investment amount of Sichuan Province (CNY)": 147274301.44, "Sichuan Province ranking": 10} |
hard001 | In 2022, a strategic consulting firm was commissioned by a provincial government to quantitatively rank the comprehensive attractiveness of pharmaceutical manufacturing across provinces, in order to identify priority target regions for attracting leading enterprises. The company designed a four-dimensional weighted sco... | 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" | 0.92 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter records with industry=\"Pharmaceutical Manufacturing\" from regional_industry_status.csv, extract province, total enterprises, total R&D expenditure, total operating revenue, total R&D personnel, and total employees; 34 provincial records were found.",
"Filter records with industry=\"Pharmaceutical Manufa... | 7 | {"National total pharmaceutical manufacturing enterprises": 449.0, "National total pharmaceutical manufacturing-related policies": 80, "Number of valid provinces": 16, "Shanghai industry agglomeration": 0.1203, "Shanghai R&D intensity": 0.2548, "Shanghai policy support": 0.1375, "Shanghai talent density": 0.162, "Shang... |
hard002 | In 2022, conduct a quantitative assessment of the investment value of the semiconductor industry across provinces. The evaluation framework requires incorporating three dimensions: first, industry scale (40% weight), measured by the inter-provincial rank percentile of total operating revenue in each province; second, p... | 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" | 0.67 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter records with industry=\"Semiconductor Industry\" from regional_industry_status.csv, extract province, total operating revenue, total operating profit, and total R&D expenditure; 34 records were found.",
"Filter enterprises with industry=\"Semiconductor Industry\" from company_profile.csv, extract company ... | 7 | {"Number of valid provinces": 13, "Zhejiang Province industry scale rank percentile": 0.6667, "Zhejiang Province profitability rank percentile": 0.5, "Zhejiang Province innovation output rank percentile": 0.8333, "Zhejiang Province composite score": 0.6667} |
hard003 | In 2022, an automotive manufacturing enterprise commissioned a third-party institution to score and rate the industrial supporting capacity of each province before selecting a site for a new plant. The scoring rules are as follows: first, rank provinces in descending order by the number of government policies related t... | Answer format: numerical value (4 decimal places). Output only the number, without units or text. If relevant data cannot be found, please answer "No relevant data found" | 0.3187 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter policy records from policy_release_status.csv where industry field contains \"Automotive Manufacturing\"; 69 records found. Group by province to count policy numbers per province (excluding \"National\" level), sort by policy count descending; top 5 provinces by policy support are ['Guangdong Province', 'Sh... | 7 | {"National total automotive manufacturing enterprises": 230.0, "National total automotive manufacturing employees": 3254510.0, "Top 5 provinces by policy": ["Guangdong Province", "Shanghai", "Hunan Province", "Sichuan Province", "Chongqing"], "Guangdong Province upstream-downstream enterprise density": 0.1174, "Guangdo... |
hard004 | In 2022, a provincial development and reform commission, when reviewing the effectiveness of fiscal subsidies for the chemical raw materials and chemical products manufacturing industry, needed to identify enterprises with misallocated subsidy resources. Specifically, analysts must first define the scope: only examine ... | The answer should be a percentage value with 2 decimal places. Output only the number, without the % symbol or text. If relevant data cannot be found, please answer "No relevant data found" | 23.18 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter policy records from policy_release_status.csv where industry field contains \"Chemical Raw Materials and Chemical Products Manufacturing\"; 60 records found. Extract province field, remove nulls and exclude \"National\" level; 23 policy-covered provinces: ['Shanghai', 'Yunnan Province', 'Inner Mongolia Auto... | 7 | {"Number of policy-covered provinces": 23, "Total chemical enterprises": 364, "Number of valid samples": 362, "Median government subsidy (yuan)": 10019029.08, "Median operating profit margin (%)": 10.0, "Valid enterprises in policy-covered provinces": 233, "High subsidy low output enterprises": 54, "Proportion (%)": 23... |
hard005 | 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 calcula... | 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" | 63.74 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter policy records from policy_release_status.csv where industry field contains \"Information Transmission, Software and Information Technology Services\"; 206 records found. Group by province to count policy numbers per province.",
"Filter enterprise records with industry=\"Information Transmission, Software... | 7 | {"Total information technology-related policies": 206, "Total information technology services enterprises": 644, "Number of valid enterprises": 432, "Number of valid provinces": 28, "Hong Kong SAR raw innovation efficiency": 63.736, "Hong Kong SAR policy support coefficient": 0.0, "Hong Kong SAR adjusted innovation eff... |
hard006 | In 2022, to measure the impact of different ownership backgrounds on the operating performance of specialized equipment manufacturing enterprises, an analysis team compared each enterprise's return on equity (ROE) level with the industry-wide return level in its province to calculate "excess ROE" as a relative performa... | The answer should be a percentage value with 2 decimal places. Output only the number, without the % symbol or text. If relevant data cannot be found, please answer "No relevant data found" | ["Collective Enterprise", 5.17] | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter enterprise records with industry=\"Specialized Equipment Manufacturing\" from company_profile.csv, extract company name, bmCode, ownership, and province; 447 enterprises found.",
"Join with company_operation_status.csv via bmCode to extract net profit, total assets, total liabilities, and operating revenu... | 7 | {"Total specialized equipment manufacturing enterprises": 447, "Number of valid enterprises": 444, "Enterprises matched with provincial data": 389, "Number of ownership types": 6, "Collective enterprise count": 2, "Collective enterprise mean excess ROE (%)": 5.17} |
hard007 | In 2022, when a research institution was reviewing the implementation effectiveness of provincial industrial policies in the food and beverage industry, it found that although some provinces had issued many support policies, the profitability of enterprises within their jurisdictions was not ideal. To identify such "po... | The answer should be a percentage value with 2 decimal places. Output only the number, without the % symbol or text. If relevant data cannot be found, please answer "No relevant data found" | 0.59 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter policy records with industry field containing \"Food and Beverage Industry\" from policy_release_status.csv, 16 records in total. Group by province field to count policy numbers per province; 4 national-level policies need to be added to each province. After adding national-level policy count to each provin... | 7 | {"Total food and beverage industry policies": 16, "Provinces with >=3 policies": ["Yunnan", "Sichuan", "Ningxia", "Hebei", "Henan", "Hainan", "Hunan", "Gansu", "Guizhou"], "Number of valid enterprises": 247, "Hainan total operating profit": 78834917.61, "Hainan total operating revenue": 13274274000.99, "Hainan operatin... |
hard008 | 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... | 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" | 4 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter all provincial records with industry=\"Electricity, Heat, Gas and Water Production and Supply\" from regional_industry_status.csv, extract province, median year-over-year change in operating revenue, total company market cap, total operating revenue amount, and number of enterprises; 34 records in total.",
... | 7 | {"Number of valid provinces": 16, "National median P/S ratio": 1.024358, "National average enterprise R&D investment ratio (%)": 1.147, "Number of high-growth provinces": 15, "Number of high-growth, low-valuation provinces": 7, "Number of provinces meeting all conditions": 4} |
hard009 | In 2022, an investment manager at a merger and acquisition fund was seeking "high R&D, low valuation" M&A targets in the textile, footwear and apparel industry, but the scope was limited to provinces covered by textile, footwear and apparel industry-related policies. The prerequisite for screening valid enterprises is:... | 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" | 9 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter policy records with industry field containing \"Textile, Footwear and Apparel\" from policy_release_status.csv, 21 records in total. Extract province field, remove nulls and exclude \"National\" level, to obtain 11 policy-covered provinces: ['Shanghai', 'Sichuan', 'Shandong', 'Guangdong', 'Guangxi', 'Xinjia... | 8 | {"Number of policy-covered provinces": 11, "Total textile, footwear and apparel enterprises": 177, "Number of valid enterprises": 81, "Median R&D investment ratio": 2.8, "Median P/E": 23.13, "Valid enterprises in policy-covered provinces": 29, "Number of enterprises meeting conditions": 9} |
hard010 | In 2022, to quantify the comprehensive competitive strength of the construction industry across regions, an industry association constructed a provincial competitiveness index system. The index is composed of four weighted sub-dimensions: market size share of national total (weight 30%), asset operation efficiency i.e.... | The answer should be a numeric 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" | 0.71 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter all provincial records with industry=\"Construction\" from regional_industry_status.csv, extract province, total operating revenue amount, total operating profit amount, total assets, total cumulative Chinese invention patent grants, number of enterprises, total R&D personnel count, and total employee count... | 7 | {"Number of valid provinces": 16, "National total construction enterprises": 148, "First-ranked province": "Beijing", "First-ranked score": 0.7287, "Last-ranked province": "Liaoning", "Last-ranked score": 0.0142, "Difference": 0.7145} |
hard011 | In 2022, a think tank was commissioned to study the impact of policy intervention on R&D behavior in the communication transmission equipment industry. The research design divides all enterprises with R&D investment ratio data records into two groups: one group from provinces that have appeared in policy release inform... | The answer should be a numeric value with 2 decimal places. A positive number indicates policy-covered provinces are higher; a negative number indicates non-policy-covered provinces are higher. Output only the number, without units or text. If relevant data cannot be found, please answer "No relevant data found" | 4.9 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter policy records with industry field containing \"Communication Transmission Equipment\" from policy_release_status.csv, 70 records in total. Extract unique province values and exclude \"National\" to obtain 17 policy-covered provinces: ['Anhui', 'Shandong', 'Guangdong', 'Sichuan', 'Hubei', 'Fujian', 'Jiangxi... | 7 | {"Number of communication transmission equipment policies": 70, "Policy-covered provinces": ["Anhui", "Shandong", "Guangdong", "Sichuan", "Hubei", "Fujian", "Jiangxi", "Chongqing", "Hunan", "Yunnan", "Guizhou", "Henan", "Shaanxi", "Hainan", "Beijing", "Shanghai", "Xinjiang"], "Number of communication transmission equip... |
hard012 | In 2022, an antitrust research team analyzed the provincial market structure of the metal smelting and rolling processing industry. To ensure statistical reliability, only provinces with operating revenue amount records and at least 5 enterprises in the industry within the jurisdiction were included. Among qualifying p... | The answer should be a percentage value with 2 decimal places. Output only the number, without the % symbol or text. If relevant data cannot be found, please answer "No relevant data found" | 4.14 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter enterprise records with industry=\"Metal Smelting and Rolling Processing\" from company_profile.csv, extract company name, bmCode, and province fields; 145 enterprises found.",
"Join with company_operation_status.csv via bmCode to extract operating revenue amount field; 145 records after merge.",
"Filte... | 7 | {"Number of metal smelting and rolling processing enterprises": 145, "Enterprises with non-null operating revenue": 111, "Number of valid provinces (enterprises >= 5)": 13, "Province with highest HHI": "Shanghai", "HHI value": 88.47, "Shanghai operating profit margin (%)": 4.14} |
hard013 | In 2022, a provincial industry and information department sought to evaluate the government subsidy utilization efficiency of enterprises of different sizes in the rubber and plastic products industry. After dividing enterprises into three groups by total assets—large (top 1/3 rounded up), medium (middle 1/3 rounded up... | The answer should be a numeric 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" | ["Large", 166.33] | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter all enterprise records with industry=\"Rubber and Plastic Products\" from company_profile.csv, extract company name, bmCode, and province fields; 107 enterprises found.",
"Join with company_operation_status.csv via bmCode to extract total assets, operating revenue amount, and government reward funds and s... | 7 | {"National total rubber and plastic enterprises": 107, "Number of valid enterprises": 107, "Small group enterprise count": 35, "Medium group enterprise count": 36, "Large group enterprise count": 36, "Small group efficiency": 95.58, "Medium group efficiency": 161.13, "Large group efficiency": 166.33, "Highest efficienc... |
hard014 | In 2022, a technology innovation fund evaluated the "R&D-patent conversion" full-chain efficiency of the consumer electronics and electrical industry across provinces, seeking to identify the province with optimal conversion efficiency (only provinces with valid enterprise count >= 3 are included). What is the R&D-pate... | The answer should be a numeric 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" | 47.29 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter all enterprise records with industry=\"Consumer Electronics and Electrical\" from company_profile.csv, extract company name, bmCode, and province fields; 358 enterprises found.",
"Join with company_operation_status.csv via bmCode to extract annual Chinese invention patent applications, annual Chinese inve... | 7 | {"National total consumer electronics and electrical enterprises": 358, "Number of valid enterprises": 266, "Number of valid provinces": 13, "Shandong patent applications": 24694.0, "Shandong patent grants": 15143.0, "Shandong R&D output density": 77.1105, "Shandong conversion efficiency": 47.29} |
hard015 | In 2022, a provincial government evaluated the comprehensive financial health of real estate enterprises to decide which provinces (where the province has an effective enterprise count >= 3) should face strengthened risk supervision for real estate firms. What is the health score of the province with the lowest financi... | The answer should be a numerical value with 2 decimal places. Output only the number without units or text explanation. If relevant data cannot be found, please answer "No relevant data found" | 0.07 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"Filter records with industry=\"房地产业\" from company_profile.csv; extract enterprise name, bmCode, and province — 295 enterprises.",
"Join with company_operation_status.csv on enterprise name and bmCode for year=2022; extract net profit amount, operating revenue amount, asset-liability ratio, and year-over-year ch... | 8 | {"real_estate_enterprises_profile_merged_2022": 295, "enterprise_records_province_aggregation_no_al_ratio_exclusion": 295, "valid_provinces_count_enterprises_ge_3": 17, "Beijing_raw_profitability": -1.0774, "Beijing_raw_solvency": -21.9888, "Beijing_raw_growth_capability": -0.1341, "Beijing_financial_health": 0.0713} |
hard016 | In 2022, an institutional investor plans to build an equity portfolio among Haishan Chang Industrial Equipment Company, Zhongbai Jinmao Chain Company, and Sansan Dateng Heavy Industry Company. The total portfolio weight must equal 1, the portfolio-weighted asset-liability ratio must equal exactly 45%, and the portfolio... | Answer format: weight of Haishan Chang Industrial Equipment Company, weight of Zhongbai Jinmao Chain Company, weight of Sansan Dateng Heavy Industry Company, weighted ROE. The first three weights to four decimal places; weighted ROE to three decimal places. Output numbers and commas only, with no explanatory text. If r... | [0.1318, 0.4954, 0.3728, 10.376] | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"From company_operation_status.csv, filter by bmCode for Haishan Chang Industrial Equipment Company (100071), Zhongbai Jinmao Chain Company (100120), and Sansan Dateng Heavy Industry Company (100260) to obtain their 2022 records; 3 valid rows found. Extract total assets, total liabilities, year-on-year change in op... | 6 | {"Firm count": 3, "Haishan Chang Industrial Equipment Company asset-liability ratio": 86.388, "Zhongbai Jinmao Chain Company asset-liability ratio": 57.6074, "Sansan Dateng Heavy Industry Company asset-liability ratio": 13.6112, "Haishan Chang Industrial Equipment Company weight": 0.1318, "Zhongbai Jinmao Chain Company... |
hard017 | In 2022, in the chemical raw materials and chemical products manufacturing industry covered by the Implementation Plan for "Three Products" in Raw Materials Industry, Hualu Runyuan Technology Co., Ltd. plans to restore profitability through product upgrade and price increases. After implementing the "Three Products" re... | Answer format: minimum price increase rate. Four decimal places. Output the number only, no percent sign or text. If relevant data cannot be found, answer "No relevant data found". | 14.2792 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"From policy_resource.jsonl, confirm that the Implementation Plan for \"Three Products\" in Raw Materials Industry specifies special support and subsidy of 5,000,000 yuan.",
"From company_profile.csv, filter record with bmCode=100639; confirm Hualu Runyuan Technology belongs to chemical raw materials and chemical... | 6 | {"Operating revenue (yuan)": 664310105.79, "Net profit (yuan)": -109823137, "Process improvement profit gain (yuan)": 9964651.59, "Subsidy profit gain (yuan)": 5000000, "Remaining profit gap (yuan)": 94858485.41, "Minimum price increase rate (%)": 14.2792} |
hard018 | In 2022, does Lianji Chuangji Machine Tool Company meet the basic conditions under the Several Policies on Supporting the Construction of a Strong Province of Skilled Workers? If yes, treat it as a sample firm eligible for skills training subsidies and apply the following: all R&D personnel receive individual skill imp... | Answer format: the number of basis points of decline. Two decimal places. Output the number only, no units or text. If relevant data cannot be found, answer "No relevant data found". | 43.33 | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, confirm Lianji Chuangji Machine Tool Company is located in Anhui Province, satisfying the geographic condition for Anhui's local skills policy.",
"From policy_resource.jsonl, locate the Notice of Anhui Provincial People's Government on Several Policies Supporting the Construction of a S... | 7 | {"Total employees": 1276, "R&D personnel count": 290, "Non-R&D employee count": 986, "Total new subsidies (yuan)": 4901000, "Adjusted R&D investment (yuan)": 53456098.35, "Adjusted R&D ratio (%)": 4.9367, "Decline (basis points)": 43.33} |
hard019 | 2022年，以山安泽医疗科技公司具有“微生态活菌业务”和“高温合金业务”双主业特征。某基金经理希望用以山安泽医疗科技公司与三三达腾重工公司构建一个两股票组合，来替代连机创机机床公司的增长暴露，并进一步检验该替代组合在剔除补贴后的盈利质量与研发强度溢价。若组合要求加权营业收入同比增减幅恰好等于连机创机机床公司2022年的对应指标，请基于本地数据计算：以山安泽医疗科技公司的组合权重、剔除政府奖励资金和补贴后的组合加权净利率，以及该组合研发投入占比相对连机创机机床公司高出的基点数。 | 答案格式为：以山安泽医疗科技公司权重,剔除补贴后的组合加权净利率,研发投入占比高出的基点数。前两项按百分比口径保留2位小数，最后一项保留2位小数。仅输出数字和逗号，不要添加单位或文字说明。如无法找到相关数据，请回答“未查询到相关数据”。 | [38.58, 14.82, 708.28] | {
"db": "bm_rag_qa",
"level": "hard",
"category": "comprehensive_decision"
} | [
"从company_core.jsonl中定位以山安泽医疗科技公司，确认其核心竞争力描述同时覆盖微生态活菌业务与高温合金业务，满足题目中的双主业前提。",
"从company_operation_status.csv中筛选bmCode分别为764661、100260、100791且year=2022的记录，提取营业收入同比增减幅、净利润金额、营业收入金额、政府奖励资金、补贴和研发投入占比字段。其中，以山安泽医疗科技公司的研发投入占比字段值为18.11%，三三达腾重工公司的研发投入占比字段值为8.90%，连机创机机床公司的研发投入占比字段值为5.37%。",
"得到以山安泽医疗科技公司营业收入同比增减幅20.92%，三... | 6 | {"以山安泽医疗科技公司权重(%)": 38.58, "三三达腾重工公司权重(%)": 61.42, "以山安泽医疗科技公司剔除补贴后净利率(%)": 9.89, "三三达腾重工公司剔除补贴后净利率(%)": 17.91, "剔除补贴后的组合加权净利率(%)": 14.82, "组合研发投入占比(%)": 12.45, "相对连机创机机床公司高出的基点数": 708.28} |
medium001 | For 2022 pharmaceutical manufacturing industry data by province, if R&D funding intensity is measured as each province's total R&D expenditure as a percentage of its total operating revenue, among all provinces with complete data records, what is the specific value of this ratio for the province with the highest level?... | The first answer is a numeric value (2 decimal places), unit is %; the second answer is the full company name, which must exactly match the "Company Name" field in company_profile.csv. If either question cannot be answered, respond with "No relevant data found". | [25.48, "Kangsheng Anjian Biopharmaceutical Company"] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter industry=\"Pharmaceutical Manufacturing\", extract province, total R&D expenditure, total operating revenue; exclude records with missing total R&D expenditure or total operating revenue, or with total operating revenue ≤ 0, yielding 16 valid province records.",
"For eac... | 5 | {"Province with highest R&D funding intensity": "Shanghai", "Shanghai total R&D expenditure (yuan)": 40798081760.73, "Shanghai total operating revenue (yuan)": 160133198188.25, "Provincial R&D funding intensity (%)": 25.48, "Company with highest R&D funding intensity in that province": "Kangsheng Anjian Biopharmaceutic... |
medium002 | 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 tot... | Two answers required, both numeric values (2 decimal places), unit is %. If relevant data cannot be found, respond with "No relevant data found". | [31.4, 6.22] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter records with industry=\"Semiconductor Industry\", extract province, total enterprise count, total operating profit; 34 province records obtained.",
"From national_industry_status.csv, filter records with industry=\"Semiconductor Industry\", extract total enterprise count... | 5 | {"Province with highest enterprise concentration": "Guangdong Province", "Guangdong semiconductor industry enterprise count": 54, "National semiconductor industry enterprise count": 172, "Enterprise concentration (%)": 31.4, "Guangdong semiconductor industry total operating profit (yuan)": 25562691329.46, "National sem... |
medium003 | In 2022, measuring per capita output efficiency of automobile manufacturing by province using revenue per capita (total operating revenue ÷ total employee count), among all provinces nationwide, what is the specific value in yuan per person for the province with the highest indicator? Compared to the national average, ... | Two answers required: first is a numeric value (2 decimal places), unit yuan/person; second is a percentage (1 decimal place), unit %. If relevant data cannot be found, respond with "No relevant data found". | [3898878.23, 175.0] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter all province records with industry=\"Automobile Manufacturing\", extract province, total operating revenue, total employee count; 34 records obtained.",
"Filter province records with non-null total operating revenue and total employee count, and total employee count > 0;... | 5 | {"Beijing total operating revenue (yuan)": 341596317171.5, "Beijing total employee count": 87614, "Beijing per capita revenue (yuan/person)": 3898878.23, "National total operating revenue (yuan)": 4614449954119.47, "National total employee count": 3254510, "National average per capita revenue (yuan/person)": 1417863.2,... |
medium004 | In 2022, rank provinces by profitability in chemical raw materials and chemical products manufacturing. Provincial operating profit margin is computed as total operating profit divided by total operating revenue. Using this as the ranking criterion, what is Guangdong Province's rank? Apply the same ranking to all relev... | Two answers required: first is Guangdong Province's rank in the provincial ranking (integer, e.g. "6" means 6th place); second is the full name of the top-ranked enterprise in Guangdong, which must match the "Company Name" field in company_profile.csv. If relevant data cannot be found, respond with "No relevant data fo... | [6, "Hengyi Changhua Technology Co., Ltd."] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter province records with industry=\"Chemical Raw Materials and Chemical Products Manufacturing\", extract province, total operating profit, total operating revenue; 34 records obtained.",
"Filter records with non-null total operating profit and total operating revenue, and ... | 5 | {"Guangdong total operating profit (yuan)": 11690448651.68, "Guangdong total operating revenue (yuan)": 101800752670.91, "Guangdong operating profit margin (%)": 11.4837, "Guangdong provincial rank": 6, "Top-ranked enterprise in Guangdong": "Hengyi Changhua Technology Co., Ltd.", "Top enterprise operating profit (yuan)... |
medium005 | 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 ... | 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" | 12.6 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all enterprise records with industry=\"Food and Beverage\" and ownership=\"Private Enterprise\" from company_profile.csv, extract enterprise name, bmCode and province fields, finding 161 food and beverage private enterprises.",
"Join with company_operation_status.csv via bmCode to obtain 2022 data for the... | 5 | {"Inner Mongolia food and beverage private enterprise total subsidies (yuan)": 1259874619.23, "Inner Mongolia food and beverage private enterprise total subsidies (hundred million yuan)": 12.6} |
medium006 | In 2022, a local government planned to introduce support policies for the specialized equipment manufacturing industry and needed to understand the province's R&D personnel investment level in this industry. Is the average proportion of R&D personnel to total employees in specialized equipment manufacturing enterprises... | The answer should be "Yes" or "No". If relevant data cannot be found, please answer "No relevant data found" | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter records with industry=\"Specialized Equipment Manufacturing\" and province=\"Zhejiang\" from regional_industry_status.csv, extract average R&D personnel proportion field; Zhejiang's average R&D personnel proportion is 18.25%.",
"Filter records with industry=\"Specialized Equipment Manufacturing\" from nat... | 4 | {"Zhejiang average R&D personnel proportion (%)": 18.25, "National average R&D personnel proportion (%)": 20.1} |
medium007 | In 2022, analyze government subsidy leverage in the information transmission, software and information technology services industry. Define government subsidy leverage effect as the ratio of each province's total operating profit to total government subsidies. What is the specific ratio for the province with the highes... | Two answers required: first is a numeric value (2 decimal places, unitless ratio); second is the full company name. If relevant data cannot be found, respond with "No relevant data found". | [67.19, "Dongche Kexin Systems Company"] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, filter industry=\"Information Transmission, Software and Information Technology Services\", extract company name, bmCode, and province.",
"Inner-join with company_operation_status.csv on year=2022 by company name and bmCode to obtain the 2022 enterprise sample for this industry (644 rec... | 5 | {"Provincial aggregation note": "Aggregate by province from the enterprise table; do not use Jiangxi totals missing from the regional table", "Jiangxi total operating profit (yuan)": 93463073.13, "Jiangxi total government rewards and subsidies (yuan)": 1391005.09, "Jiangxi government subsidy leverage effect": 67.19, "E... |
medium008 | In 2022, to study the capital turnover of central state-owned enterprises in the electricity, heat, gas and water production and supply industry, calculate the asset turnover ratio for each enterprise by dividing its annual operating revenue by its total assets. Find the arithmetic mean of the asset turnover ratios for... | The answer should be a numerical value (rounded to 4 decimal places). If the relevant data cannot be found, please answer "No relevant data found" | 0.3266 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter records from company_profile.csv where industry=\"Electricity, heat, gas and water production and supply\" and ownership=\"Central state-owned enterprise\", extract company name and bmCode fields, finding 44 enterprises in total.",
"Join with company_operation_status.csv by bmCode to retrieve 2022 data fo... | 5 | {"Sum of Asset Turnover Ratios": 14.369275, "Number of Valid Enterprises": 44, "Average Asset Turnover Ratio": 0.3266} |
medium009 | In 2022, a mining industry enterprise plans to go public for financing and hopes to list on the exchange with the highest average market capitalization among enterprises in this industry. Among the four exchanges—Shenzhen Stock Exchange, Hong Kong Stock Exchange, Shanghai Stock Exchange, and Beijing Stock Exchange—whic... | The answer should be the exchange name (e.g., "Shenzhen Stock Exchange", "Hong Kong Stock Exchange", "Shanghai Stock Exchange", "Beijing Stock Exchange"). If the relevant data cannot be found, please answer "No relevant data found" | Shanghai Stock Exchange | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter records from company_profile.csv where industry=\"Mining\", extract company name, bmCode and exchange fields, finding 143 mining enterprises in total.",
"Join with company_operation_status.csv by bmCode to retrieve 2022 data for these enterprises, extract company market capitalization field.",
"Filter r... | 5 | {"Shanghai Stock Exchange Total Market Capitalization of Mining Enterprises (billion CNY)": 47718.0, "Number of Mining Enterprises on Shanghai Stock Exchange": 49, "Shanghai Stock Exchange Average Market Capitalization of Mining Enterprises (billion CNY)": 973.84} |
medium010 | In 2022, in the provincial data for the construction industry, each province has an indicator reflecting the average asset-liability ratio (financial leverage level) of enterprises in that province's industry (considering only enterprises with valid total assets and total liabilities). Among the provinces covered by va... | The answer should be a numerical value (rounded to 2 decimal places), in units of %. If the relevant data cannot be found, please answer "No relevant data found" | ["Shanxi Province", 27.17] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter records from company_profile.csv where industry=\"Construction\", extract company name, bmCode and province fields, finding 148 enterprises in total.",
"Join with company_operation_status.csv by bmCode, extract total liabilities and total assets fields, resulting in 148 records after merging.",
"Filter ... | 5 | {"Total Number of Construction Enterprises": 148, "Number of Valid Enterprises (total liabilities and total assets not empty)": 148, "Number of Valid Provinces": 22, "Shanxi Province Mean Asset-Liability Ratio (%)": 27.17} |
medium011 | In 2022, among all enterprises in the rubber and plastic products industry with R&D investment records, what is the R&D concentration CR5? | The answer should be a numerical value (rounded to 2 decimal places), in units of %. If the relevant data cannot be found, please answer "No relevant data found" | 34.66 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter records from company_profile.csv where industry=\"Rubber and plastic products\", extract company name and bmCode fields, finding 107 enterprises in total.",
"Join with company_operation_status.csv by bmCode to retrieve 2022 data for these enterprises, extract R&D investment amount field.",
"Filter recor... | 5 | {"Sum of R&D Investment Amount of Top 5 Enterprises (CNY)": 4221126553.77, "Total R&D Investment Amount of the Industry (CNY)": 12179847530.98, "R&D Concentration CR5 (%)": 34.66} |
medium012 | In 2022, among all enterprises in Guangdong Province belonging to the wholesale and retail trade industry, using each enterprise's net profit margin as the comparison standard, what is the indicator value for the enterprise with the highest net profit margin? What is that enterprise's rank among all enterprises in this... | Two answers required: first is a numeric value (2 decimal places, unit %); second is the rank number (integer, e.g. "7" means 7th place). If relevant data cannot be found, respond with "No relevant data found". | [31.25, 7] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, filter all enterprise records with industry=\"Wholesale and Retail Trade\" and province=\"Guangdong Province\", extract company name and bmCode; 43 Guangdong wholesale and retail enterprises found.",
"From company_operation_status.csv, join 2022 data by bmCode for these enterprises, ext... | 5 | {"Yonghui Changda Wholesale Company net profit (yuan)": 292221119.71, "Yonghui Changda Wholesale Company operating revenue (yuan)": 935248730.59, "Yonghui Changda Wholesale Company net profit margin (%)": 31.25, "Yonghui Changda Wholesale Company nationwide rank": 7} |
medium013 | 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 ... | 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 t... | [13.81, 23] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter all records with industry=\"Scientific Research and Technical Services\", extract province and median year-on-year net profit growth rate; 34 province records found.",
"Filter province records with non-null median year-on-year net profit growth rate; 16 valid provinces."... | 5 | {"Valid province count for scientific research and technical services (non-null median YoY net profit growth)": 16, "Anhui Province median year-on-year net profit growth rate (%)": 13.81, "Enterprise with highest indicator in Anhui Province": "Zhongqi Shengyuan Technology Research Institute", "Enterprise year-on-year n... |
medium014 | In 2022, for the metal smelting and rolling processing industry, among provinces with valid records for both total government subsidies and total industry employee count, per capita subsidy is computed as each province's total government rewards and subsidies divided by that province's industry employee count. What is ... | Two answers required: first is a numeric value (2 decimal places, unit yuan/person), i.e. the highest provincial per capita subsidy; second is a rank number (integer), indicating the nationwide rank of the enterprise with the highest indicator in that province among all enterprises in this industry. If relevant data ca... | [17569.95, 12] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter all province records with industry=\"Metal Smelting and Rolling Processing\", extract province, total government rewards and subsidies, total employee count; 34 province records obtained.",
"Filter records with non-null total government rewards and subsidies and total em... | 5 | {"Shanghai total government rewards and subsidies (yuan)": 893080778.37, "Shanghai total employee count": 50830.0, "Shanghai per capita subsidy (yuan/person)": 17569.95, "Enterprise with highest indicator in Shanghai": "Xin Ge Jinze Materials Company", "Enterprise per capita subsidy (yuan/person)": 31941.25, "Enterpris... |
medium015 | List the 2022 indicators for which Shandong Province's financial industry enterprise averages are below the national financial industry medians. | The answer must list all qualifying indicator names, separated by semicolons. If relevant data cannot be found, respond with "No relevant data found". | ["Year-on-year R&D personnel growth rate", "Year-on-year operating profit growth rate", "Year-on-year net profit growth rate", "Year-on-year employee growth rate", "Capitalized R&D expenditure", "Year-on-year capitalized R&D expenditure growth rate", "Annual PCT patent applications", "Annual PCT invention patent applic... | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter records with industry=\"Financial Industry\" and province=\"Shandong Province\", extract total enterprise count; 12 Shandong financial industry enterprises found.",
"From national_industry_status.csv, filter records with industry=\"Financial Industry\" and district=\"Nat... | 5 | {"Shandong Province financial industry enterprise count": 12, "National financial industry enterprise count": 297, "Indicator count below national median": 28, "Main indicator list": ["Year-on-year R&D personnel growth rate", "Year-on-year operating profit growth rate", "Year-on-year net profit growth rate", "Year-on-y... |
medium016 | In 2022, between Sichuan Province's top enterprise by operating revenue and Shandong Province's top enterprise by net profit in the pharmaceutical manufacturing industry, which one has the highest tax payment? | The answer must be the company name. Output only the company name, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | No relevant data found | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, filter all enterprise records with province=\"Sichuan Province\", extract company name and bmCode; 198 Sichuan enterprises found.",
"From company_operation_status.csv, filter 2022 data for these enterprises by company name and bmCode, extract operating revenue; sort by operating revenue... | 5 | {"Tax payment field exists": false} |
medium017 | In 2022, the industry where Zhongbai Jinmao Chain Company operates, is the enterprise with the highest year-on-year R&D expenditure growth rate also the one with the highest R&D expenditure? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, find the record for Zhongbai Jinmao Chain Company, extract industry field; industry is \"Wholesale and Retail Trade\". From company_profile.csv, filter all enterprise records with industry=\"Wholesale and Retail Trade\", extract company name and bmCode; 273 wholesale and retail enterprise... | 5 | {"Enterprise with highest year-on-year R&D expenditure growth rate": "Yonghui Zesheng Chain Company", "Highest growth rate enterprise YoY R&D expenditure growth rate (%)": 2221.3, "Highest growth rate enterprise R&D expenditure (yuan)": 516766.56, "Enterprise with highest R&D expenditure": "Bubusheng Jin Commerce Compa... |
medium018 | In 2022 Nationwide, is the province with the highest R&D expenditure growth rate also the province with the lowest R&D expenditure? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, read R&D expenditure data for all provinces, including province, total R&D expenditure, average year-on-year R&D expenditure growth rate, etc.",
"Aggregate total R&D expenditure and average year-on-year R&D expenditure growth rate by province; exclude provinces with total R&D e... | 5 | {"Province with highest R&D expenditure growth rate": "Hong Kong Special Administrative Region", "Highest R&D expenditure growth rate (%)": 212.35, "Highest growth province total R&D expenditure (yuan)": 14248827635.96, "Province with lowest R&D expenditure": "Jilin Province", "Lowest R&D expenditure (yuan)": 857429426... |
medium019 | In 2022, Sichuan Province, is Zhongbai Jinmao Chain Company's R&D expenditure higher than the R&D expenditure of the enterprise ranked 15th nationwide in its industry? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, find the record for company name=\"Zhongbai Jinmao Chain Company\", extract industry and province; industry is \"Wholesale and Retail Trade\", province is \"Sichuan Province\".",
"From company_operation_status.csv, filter 2022 data for company name=\"Zhongbai Jinmao Chain Company\", ext... | 5 | {"Zhongbai Jinmao Chain Company R&D expenditure (yuan)": 11270987.0, "15th-ranked nationwide wholesale and retail enterprise R&D expenditure (yuan)": 265616054.7, "Comparison result": "No"} |
medium020 | In 2022, the chemical raw materials and chemical products manufacturing industry in Shandong Province, is the market capitalization of the leading enterprises by operating revenue among the top 3 in this industry nationwide? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | Yes | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, filter all enterprise records with province=\"Shandong Province\" and industry=\"Chemical raw materials and chemical products manufacturing\", extract company names, identify enterprises in the chemical raw materials and chemical products manufacturing industry in Shandong Province.",
"... | 5 | {"Shandong Province operating revenue leading enterprise name": "Hengyi Changhua Fine Chemical Company", "Shandong Province operating revenue leading enterprise operating revenue (yuan)": 165565462711.66, "Shandong Province operating revenue leading enterprise company market capitalization": 2754.0, "Chemical raw mater... |
medium021 | In 2022, the chemical raw materials and chemical products manufacturing industry in Shandong Province, is the market capitalization of the enterprise with the highest operating revenue among the top 3 in this industry nationwide? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | Yes | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, filter all enterprise records with province=\"Shandong Province\" and industry=\"Chemical raw materials and chemical products manufacturing\", extract company names, identify enterprises in the chemical raw materials and chemical products manufacturing industry in Shandong Province.",
"... | 5 | {"Shandong Province operating revenue leading enterprise operating revenue (yuan)": 165565462711.66, "Shandong Province operating revenue leading enterprise company market capitalization": 2754.0, "Chemical raw materials and chemical products manufacturing nationwide market cap No.3 enterprise market capitalization": 9... |
medium022 | In 2022 is the region with the highest average R&D investment growth rate also the one with the most policy quantity? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter all provincial records, extract province and year-on-year R&D investment growth rate mean fields, obtain R&D investment growth rate data for each province and industry.",
"Aggregate R&D investment growth rate data by province, calculate the average R&D investment growth ... | 5 | {"Region with highest average R&D investment growth rate": "Hong Kong Special Administrative Region", "Region with most policies": "Guangdong Province", "Comparison result": "No"} |
medium023 | In 2022 is the average year-on-year net profit growth rate for the industry where Haishan Changgong Equipment Company operates higher than the average R&D investment growth rate? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From company_profile.csv, find the record with company name=\"Haishan Changgong Equipment Company\", extract the industry field, determine its industry as \"General equipment manufacturing\".",
"From national_industry_status.csv, filter records with industry=\"General equipment manufacturing\" and district=\"Nat... | 4 | {"Industry where Haishan Changgong Equipment Company operates": "General equipment manufacturing", "General equipment manufacturing net profit year-on-year growth rate mean (%)": -79.47492958, "General equipment manufacturing R&D investment year-on-year growth rate mean (%)": 10.1399523809524, "Comparison result": "No"... |
medium024 | In 2022, is the region with the highest total operating revenue nationwide also the one with the largest total enterprise market capitalization? | The answer must be "Yes" or "No". Output only the answer, with no additional text. If relevant data cannot be found, respond with "No relevant data found". | Yes | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"From regional_industry_status.csv, filter all provincial records (excluding \"National\"), extract province, total operating revenue amount, and total company market capitalization fields.",
"Aggregate total operating revenue amount (yuan) across all industries by province, obtain total operating revenue amount ... | 5 | {"Region with highest total operating revenue amount (yuan)": "Beijing", "Region with largest total enterprise market capitalization (yuan)": "Beijing", "Comparison result": "Yes"} |
medium025 | In 2022, is the industry with the highest R&D investment growth rate also the industry with the largest R&D investment? | The answer must be "Yes" or "No". Only output the answer, do not add any explanation. If the relevant data cannot be found, please answer "No relevant data found" | Yes | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all records with district=\"National\" from national_industry_status.csv, extract the fields: industry, year-over-year change in R&D investment (average), and total R&D investment amount.",
"Filter industry records where both the year-over-year change in R&D investment (average) and total R&D investment a... | 5 | {"Industry with the highest R&D investment growth rate": "Information transmission, software and information technology services", "Maximum R&D investment growth rate (%)": 179.78, "Industry with the largest total R&D investment amount": "Information transmission, software and information technology services", "Maximum... |
medium026 | In 2022, does the industry with the highest average asset-liability ratio in Guangdong Province belong to the industry with the highest average asset-liability ratio nationwide? | The answer must be "Yes" or "No". Only output the answer, do not add any explanation. If the relevant data cannot be found, please answer "No relevant data found" | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all records with province=\"Guangdong Province\" from regional_industry_status.csv, extract the fields: industry and average asset-liability ratio.",
"Filter industry records where the average asset-liability ratio is not empty. Sort by the average asset-liability ratio field in descending order. The indu... | 5 | {"Industry with the highest average asset-liability ratio in Guangdong Province": "Textile, footwear and apparel industry", "Industry with the highest average asset-liability ratio nationwide": "Financial industry", "Comparison result": "No"} |
medium027 | In 2022, Compare the enterprise with the highest R&D input-output ratio in Guangdong Province and the enterprise with the highest R&D input-output ratio in Sichuan Province (R&D input-output ratio = operating revenue amount / R&D investment amount). Which enterprise has higher operating revenue? The unit of operating r... | The answer must be "yes" or "no". Output only the answer, without any additional explanation. If the relevant data cannot be found, please answer "No relevant data retrieved". | The enterprise with the highest R&D input-output ratio in Guangdong Province (Wulichangyuan Wholesale Company) has higher operating revenue | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all enterprise records with province=\"Guangdong Province\" and province=\"Sichuan Province\" from company_profile.csv, and extract the enterprise name and province fields.",
"Filter all records with year=2022 from company_operation_status.csv, and extract the enterprise name, operating revenue amount, an... | 5 | {"Enterprise with highest R&D input-output ratio in Guangdong Province": "Wulichangyuan Wholesale Company", "Enterprise with highest R&D input-output ratio in Sichuan Province": "Guotouzeyuan New Energy Company", "Enterprise with higher operating revenue": "Enterprise with highest R&D input-output ratio in Guangdong Pr... |
medium028 | In 2022, for the enterprise ranked first in year-over-year growth rate of R&D investment in the chemical raw materials and chemical products manufacturing industry, which of its indicators perform below the industry average? | Output only the indicator name(s) as the answer, without any additional explanation. If the relevant data cannot be found, please answer "No relevant data retrieved" | ["Total assets", "R&D investment ratio", "Capitalized R&D investment", "Year-over-year change in capitalized R&D investment", "Company market capitalization", "Cumulative China patent applications", "Cumulative China invention patent grants", "Cumulative China invention patent invalidations", "Annual China patent appli... | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all enterprise records with industry=\"chemical raw materials and chemical products manufacturing\" from company_profile.csv, and extract the enterprise name and industry fields.",
"Filter all records with year=2022 from company_operation_status.csv, and extract the enterprise name, year-over-year change ... | 5 | {"Enterprise ranked first in R&D investment year-over-year growth rate": "Huayichangze Technology Co., Ltd.", "Indicators below industry average": ["Total assets", "R&D investment ratio", "Capitalized R&D investment", "Year-over-year change in capitalized R&D investment", "Company market capitalization", "Cumulative Ch... |
medium029 | Total number of all enterprises affected by the policy 'Notice of the General Office of Guangdong Provincial People's Government on Printing and Distributing Several Measures of Guangdong Province for Further Promoting Steady Growth of Industrial Economy' in 2022 | The answer must be "yes" or "no". Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | 416 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Search policy_resource.csv for policy records whose policy name contains \"Guangdong Province's Promotion of Steady Industrial Economic Growth\" and \"Guangdong Province\" to identify the policy.",
"Extract the industries involved from the industry field of the policy record, obtaining 8 industries: Consumer Ele... | 5 | {"Number of industries involved in the policy": 8, "Involved industries": ["Consumer Electronics and Electrical Equipment", "Automobile Manufacturing", "Textile and Footwear", "Special Purpose Equipment Manufacturing", "General Purpose Equipment Manufacturing", "Communication Transmission Equipment", "Semiconductor", "... |
medium030 | Did both the operating revenue and R&D investment of Haishan Changgong Equipment Company and Sansan Daten Heavy Industry Company show an upward trend in 2022? | The answer must be "yes" or "no". Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | no | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all records with enterprise names \"Haishan Changgong Equipment Company\" and \"Sansan Daten Heavy Industry Company\" from company_operation_status.csv, and extract the enterprise name, year, operating revenue amount, R&D investment amount, year-over-year change in operating revenue, and year-over-year chan... | 5 | {"Haishan Changgong Equipment Company year-over-year change in operating revenue (%)": -19.28, "Haishan Changgong Equipment Company year-over-year change in R&D investment (%)": -14.09, "Haishan Changgong Equipment Company trend": "Both operating revenue and R&D investment declined", "Sansan Daten Heavy Industry Compan... |
medium031 | In 2022, was Haishan Changgong Equipment Company the only enterprise in its region with both increased operating revenue and R&D investment? | The answer must be "yes" or "no". Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | no | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Look up the record for enterprise name \"Haishan Changgong Equipment Company\" in company_profile.csv, extract the province field, and obtain the region where the enterprise is located as \"Shandong Province\".",
"Filter records with enterprise name \"Haishan Changgong Equipment Company\" and year=2022 from comp... | 4 | {"Region where Haishan Changgong Equipment Company is located": "Shandong Province", "Haishan Changgong Equipment Company year-over-year change in operating revenue (%)": -19.28, "Haishan Changgong Equipment Company year-over-year change in R&D investment (%)": -14.09, "Did operating revenue increase": "No", "Did R&D i... |
medium032 | In 2022, was Haishan Changgong Equipment Company the only enterprise in its region with both declined operating revenue and R&D investment? | The answer must be "yes" or "no". Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | no | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Look up the record for enterprise name \"Haishan Changgong Equipment Company\" in company_profile.csv, extract the province field, and obtain the region where the enterprise is located as \"Shandong Province\".",
"Filter records with enterprise name \"Haishan Changgong Equipment Company\" and year=2022 from comp... | 5 | {"Region where Haishan Changgong Equipment Company is located": "Shandong Province", "Haishan Changgong Equipment Company year-over-year change in operating revenue (%)": -19.28, "Haishan Changgong Equipment Company year-over-year change in R&D investment (%)": -14.09, "Did operating revenue decline": "Yes", "Did R&D i... |
medium033 | In the industry with the most invention patent grants in 2022, what is the average asset-liability ratio of enterprises? In which province is this industry concentrated? | Answer data should retain two decimal places. Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | [85.7, "Guangdong Province"] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all records with district=\"National\" from national_industry_status.csv, and extract the industry and total cumulative China invention patent grants fields.",
"Filter industry records with non-null total cumulative China invention patent grants, sort by total cumulative China invention patent grants in d... | 5 | {"Industry with the most invention patent grants": "Consumer Electronics and Electrical Equipment", "Number of enterprises in this industry": 358, "Average asset-liability ratio (%)": 85.7, "Number of 'Consumer Electronics and Electrical Equipment' enterprises in Guangdong Province": 150} |
medium034 | Among the provinces that performed best in cultivating high-tech enterprises in 2022 (measured by the number of high-tech enterprises), which high-tech enterprise has the highest year-over-year growth in average operating revenue? | The answer must be an enterprise name. Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | Langji Ruanchuang Information Technology Company | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Identify high-tech enterprises from company_profile.csv: enterprises whose firstClassification and secondClassification fields contain keywords such as \"technology\", \"innovation\", \"R&D\", or whose industry field contains keywords such as \"technology\", \"information\", \"software\", \"electronics\", \"commun... | 5 | {"Top 3 provinces with the most high-tech enterprises": ["Guangdong Province", "Beijing", "Jiangsu Province"], "Number of high-tech enterprises in Guangdong Province": 89, "Number of high-tech enterprises in Beijing": 49, "Number of high-tech enterprises in Jiangsu Province": 48, "High-tech enterprise with highest year... |
medium035 | In 2022, which provinces ranked in the top three in terms of market share among enterprises in the cloud computing services sector? | The answer must be province names. Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | ["Beijing", "Shanghai", "Guangdong Province"] | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Identify cloud computing services enterprises from company_profile.csv: enterprises with secondClassification=\"Internet and cloud computing, big data services\" or containing keywords such as \"cloud computing\", \"cloud services\", \"cloud platform\".",
"Build a mapping from enterprise name to province from co... | 5 | {"Number of enterprises in cloud computing services sector": 9, "Total operating revenue (yuan)": 81064346518.77, "Top 3 provinces by market share": ["Beijing", "Shanghai", "Guangdong Province"], "Beijing market share (%)": 93.92, "Number of enterprises in Beijing": 3, "Shanghai market share (%)": 2.43, "Number of ente... |
medium036 | In 2022, what percentage of total operating revenue in the market do the top 20% enterprises by R&D investment in Sichuan Province's pharmaceutical manufacturing industry account for? | The answer must be an exact number with 2 decimal places. Output only the number, do not add units, commas, or any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | 61.92 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all enterprise records with province=\"Sichuan Province\" and industry=\"Pharmaceutical Manufacturing\" from company_profile.csv, extract the enterprise name and bmCode fields, and find 15 pharmaceutical manufacturing enterprises in Sichuan Province.",
"Filter 2022 data for these enterprises from company_... | 5 | {"Sum of operating revenue of top 20% enterprises (yuan)": 22527376804.67, "Sum of operating revenue of all enterprises (yuan)": 36382939883.72, "Percentage": 61.92} |
medium037 | In 2022, what percentage of total operating revenue in the market do the top enterprises by R&D investment (top 3) in Sichuan Province's pharmaceutical manufacturing industry account for? | The answer must be an exact number with 2 decimal places. Output only the number, do not add units, commas, or any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | 61.92 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter all enterprise records with province=\"Sichuan Province\" and industry=\"Pharmaceutical Manufacturing\" from company_profile.csv, extract the enterprise name and bmCode fields, and find 15 pharmaceutical manufacturing enterprises in Sichuan Province.",
"Filter 2022 data for these enterprises from company_... | 5 | {"Sum of operating revenue of top 20% enterprises (yuan)": 22527376804.67, "Sum of operating revenue of all enterprises (yuan)": 36382939883.72, "Percentage": 61.92} |
medium038 | In 2022, which enterprise has the highest operating revenue in the same region and industry as Sansan Daten Heavy Industry Company? | The answer must be an enterprise name. Output only the enterprise name, do not add any other explanatory text. If relevant data cannot be found, please answer "No relevant data found" | Lingong Hangteng Heavy Industry Company | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Look up the record for Sansan Daten Heavy Industry Company in company_profile.csv, extract the province and industry fields, and determine its region as \"Beijing\" and industry as \"Special Purpose Equipment Manufacturing\".",
"Filter all enterprise records with province=\"Beijing\" and industry=\"Special Purpo... | 4 | {"Total number of special purpose equipment manufacturing enterprises in Beijing": 38, "Operating revenue of Lingong Hangteng Heavy Industry Company (yuan)": 80034467972.0, "Enterprise with highest operating revenue": "Lingong Hangteng Heavy Industry Company"} |
medium039 | In 2022, list all indicators for which Guangdong Province's Information Transmission, Software and Information Technology Services industry has mean values superior to the national average, and sort them by advantage magnitude from high to low. | Answer format: [Indicator 1, Indicator 2, Indicator 3, ...]. Output only indicator names, separated by commas and spaces, do not add any other explanatory text. If relevant data cannot be found, please answer "No relevant data found" | ["Mean of year-over-year change in R&D investment ratio", "Mean of year-over-year change in net profit", "Mean of annual PCT patent applications", "Mean of annual PCT invention patent applications", "Mean of government incentive funds and subsidies", "Mean of net profit amount", "Mean of year-over-year change in capita... | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter records with industry=\"Information Transmission, Software and Information Technology Services\" and district=\"National\" from national_industry_status.csv, extract all fields containing \"mean\" and their values, and obtain national average data. Total number of indicator fields containing mean is 48.",
... | 4 | {"Total number of national indicator fields containing mean": 48, "Total number of Guangdong Province indicator fields containing mean": 48, "Number of advantage indicators in Guangdong Province": 15, "List of advantage indicators": ["Mean of year-over-year change in R&D investment ratio", "Mean of year-over-year chang... |
medium040 | In 2022, in Guangdong Province's Raw Chemical Materials and Chemical Products Manufacturing industry, what share of the market's operating revenue does the company with the highest market capitalization account for? | The answer must be an exact number, rounded to 2 decimal places. Output only the number, do not add units, commas, or any textual explanation. If relevant data cannot be found, please answer "No relevant data found" | 21.92 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter from company_profile.csv all enterprise records with province=\"Guangdong Province\" and industry=\"Raw Chemical Materials and Chemical Products Manufacturing\", extract enterprise name and bmCode fields, finding 41 enterprises in Guangdong Province's Raw Chemical Materials and Chemical Products Manufacturi... | 5 | {"Operating revenue of highest market cap enterprise (CNY)": 22316919995.89, "Total operating revenue of Guangdong Province Raw Chemical Materials and Chemical Products Manufacturing industry (CNY)": 101800752670.91, "Share": 21.92} |
medium041 | In 2022, nationwide, is the province with the highest mean market capitalization also the province with the highest total net profit? | The answer must be "Yes" or "No". Output only the answer, do not add any other explanatory text. If relevant data cannot be found, please answer "No relevant data found" | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Extract province information for all enterprises from the province field in company_profile.csv, totaling 6895 enterprise records.",
"Extract company market capitalization and net profit amount fields for all enterprises from company_operation_status.csv, totaling 6895 enterprise records. Join company_profile.cs... | 5 | {"Province with highest mean market capitalization": "Taiwan Province", "Province with highest total net profit": "Beijing", "Comparison result": "No"} |
medium042 | In 2022, among enterprises in regions applicable to the "Notice on Organizing Applications for First Home Purchase Subsidies for Outstanding Young Talents in the Biomedicine Industry" policy, what is the net profit of the enterprise with the best operating revenue performance? | The answer must be an exact number, in CNY, rounded to 2 decimal places. Output only the number, do not add units, commas, or any textual explanation. If relevant data cannot be found, please answer "No relevant data found" | 4253373290.96 | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter from policy_release_status.csv for policy name=\"Notice on Organizing Applications for First Home Purchase Subsidies for Outstanding Young Talents in the Biomedicine Industry\", extract province field, and determine that the applicable region is \"Guangdong Province\" and the applicable industry is \"Pharma... | 5 | {"Applicable region": "Guangdong Province", "Applicable industry": "Pharmaceutical Manufacturing", "Enterprise with highest operating revenue": "Yishan Zeyuan Pharmaceutical Co., Ltd.", "Net profit amount of enterprise with highest operating revenue (CNY)": 4253373290.96} |
medium043 | In 2022, for Pharmaceutical Manufacturing, is the province with the highest total assets also the province with the highest R&D investment? | The answer must be "Yes" or "No". Output only "Yes" or "No", do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | Yes | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Filter from regional_industry_status.csv all provincial records with industry=\"Pharmaceutical Manufacturing\".",
"In the filtered results, sort by total assets in descending order. The province with the maximum total assets is \"Beijing\", with total assets of 813813599815.91.",
"In the same filtered results,... | 4 | {"Province with highest total assets in Pharmaceutical Manufacturing": "Beijing", "Province with highest total R&D investment in Pharmaceutical Manufacturing": "Beijing", "Whether the two top provinces are the same": "Yes"} |
medium044 | In 2022, in Shandong Province's Pharmaceutical Manufacturing industry, is Haishan Changgong Equipment Company's R&D investment ratio higher than the R&D investment ratio of the 10th-ranked Pharmaceutical Manufacturing enterprise in Hunan Province? | The answer must be "Yes" or "No". Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | Yes | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Search for records with enterprise name=\"Haishan Changgong Equipment Company\" in company_profile.csv. The enterprise has bmCode=100071, industry=\"General Equipment Manufacturing\", province=\"Shandong Province\".",
"Filter from company_operation_status.csv the 2022 data by enterprise name=\"Haishan Changgong ... | 5 | {"R&D investment ratio of Haishan Changgong Equipment Company (%)": 4.33, "10th-ranked enterprise in Hunan Province Pharmaceutical Manufacturing": "Ruiying Taiyuan Medical Equipment Co., Ltd.", "R&D investment ratio of 10th-ranked enterprise in Hunan Province Pharmaceutical Manufacturing (%)": 2.87, "Comparison result"... |
medium045 | In 2022, in Sichuan Province, is Zhongbai Jinmao Chain Company's R&D investment higher than the R&D investment of the 15th-ranked enterprise nationwide in its industry? | The answer must be "Yes" or "No". Output only the answer, do not add any explanatory text. If relevant data cannot be found, please answer "No relevant data found" | No | {
"db": "bm_rag_qa",
"level": "medium",
"category": "comprehensive_decision"
} | [
"Search for records with enterprise name=\"Zhongbai Jinmao Chain Company\" in company_profile.csv. The enterprise has bmCode=100120, industry=\"Wholesale and Retail Trade\", province=\"Sichuan Province\".",
"Filter from company_operation_status.csv the 2022 data by enterprise name=\"Zhongbai Jinmao Chain Company\... | 5 | {"R&D investment amount of Zhongbai Jinmao Chain Company (CNY)": 11270987.0, "15th-ranked enterprise nationwide in Wholesale and Retail Trade": "Lianhua Tongze Trading Company", "R&D investment amount of 15th-ranked enterprise nationwide in Wholesale and Retail Trade (CNY)": 265616054.7, "Comparison result": "No"} |
DataClaw
A data-analysis benchmark for OpenClaw-style end-to-end agents. Every task is grounded in real-world data and has a single objective gold answer.
🌊 Data Analysis Tasks Are Changing in the OpenClaw Era
With the emergence of end-to-end agents like OpenClaw, data analysis is no longer equivalent to static QA — "read a passage, output one answer." Real-world data analysis tasks often require agents to locate evidence across heterogeneous files, filter and join entities across tables, perform statistical and normalization calculations, verify intermediate results, and strictly follow output constraints.
This means the core difficulty of a benchmark has shifted from answer generation alone to full agent-driven execution. A truly valuable data-analysis benchmark must test not only whether the final answer is correct, but also whether the agent can reliably complete a series of steps — retrieval, filtering, computation, verification, and constraint compliance — in complex data environments.
DataClaw is designed for exactly this shift. It evaluates not abstract capability divorced from execution, but how OpenClaw-style end-to-end agents actually perform on data analysis tasks under real data conditions, explicit task constraints, and a reproducible execution protocol.
🔍 What Is DataClaw?
DataClaw is a process-oriented data-analysis benchmark for realistic, complex data environments. Its core goal is not merely to measure agents' end-task performance, but to serve as a high-fidelity testbed that also evaluates, at fine granularity, how agents evolve when facing real-world complexity and multi-step reasoning.
DataClaw simulates at scale the noisy, weakly-semantic, cross-domain data environments found in the real world. Complex data-analysis questions are authored by domain experts in finance and computer science, and each task's process annotations and unique objective answers are cross-verified by human experts with AI assistance. Process annotations include task milestones, human-corrected reference trajectories, and evidence data sources. DataClaw adopts OpenClaw as its unified agent framework.
🎯 Why DataClaw?
- From idealized data environments to imperfect real-world data environments. DataClaw contains a mix of structured and unstructured data, covering enterprise profiles, business operating status, regional industry statistics, national industry statistics, and policy texts. All data is collected from the real world and comes with friction such as missing indicators, inconsistent definitions, and inconsistent naming. Tasks face realistic data environments, not over-cleaned single-table lookups.
- From single-shot static queries to multi-step dynamic reasoning. DataClaw tasks typically require agents to complete a multi-stage chain of operations rather than producing a one-shot answer. The challenge for agents comes not only from retrieval but also from cross-source integration, metric construction, aggregation computation, and format constraint compliance.
- From outcome-oriented evaluation to process-oriented evaluation. DataClaw goes beyond simple outcome-accuracy evaluation and dissects how the agent's execution unfolds at fine granularity. Outcome-oriented evaluation paradigms focus only on final accuracy. This black-box approach ignores intermediate reasoning and provides little actionable signal for guiding optimization.
🏗️ Repository Layout
Key directories and scripts:
assets/database/: Benchmark data files, injected wholesale into the container workspace at run time. The root containsinternal_metrics.csv(internal business-logic knowledge base);enterprise/,industry/, andpolicy/hold the three theme-domain datasets.assets/qa_raw/: Raw task source files.assets/qa_gold/: Minimized gold files derived fromqa_raw.tasks/: Generated OpenClaw task spec files.dataclaw/build_tasks.py: Builder that producesqa_goldandtasks/fromqa_raw.dataclaw/eval/run_batch.py: Host-side evaluation orchestrator; one isolated container per task.dataclaw/utils/docker_utils.py: Container lifecycle management, OpenClaw onboarding, and model configuration.dataclaw/utils/grading.py: Outcome scoring (LLM-judged Acc).dataclaw/utils/process_grading.py: Process scoring (EE on correct tasks; GPR / TPE on incorrect tasks).script/docker_save_image.sh: Image build and export script.
⚙️ Evaluation Lifecycle
Each evaluation task runs in its own Docker container. The host orchestrator manages the full lifecycle:
Host (dataclaw/eval/run_batch.py)
|
+-- For each task (parallel via --parallel N):
1. docker run -> start isolated container
2. docker cp -> inject workspace files
3. docker exec -> OpenClaw onboard
4. docker exec -> start gateway (background)
5. docker exec -> set model and run agent
6. docker exec -> run llm_judge scoring
7. docker cp -> collect logs and results
8. docker rm -> remove container
🚀 User Quick Start
1. Obtain the Pre-built Image
Download the pre-built image tarball from DataClaw v0.1.0 (asset dataclaw_ubuntu_v0.1.0.tar), then load it:
docker load -i dataclaw_ubuntu_v0.1.0.tar
After loading, confirm the local image tag is dataclaw:0.1.0 and matches DOCKER_IMAGE in .env.
2. Clone This Repository
git clone <repository-url>
cd <repository-dir>
Use the actual repository URL shown on the GitHub page.
3. Install Python Dependencies
pip install pyyaml python-dotenv
pyproject.tomlrequires Python>=3.10. For a fuller local dev setup, install additional dev dependencies as you prefer.
4. Configure Environment
Copy the template:
cp .env.example .env
Edit .env and pay attention to at least the following fields:
| Variable | Required | Description |
|---|---|---|
DEFAULT_MODEL |
Yes | Model under test, e.g. openrouter/anthropic/claude-sonnet-4.6 |
OPENROUTER_API_KEY |
One of two | Used when the main model or judge is called via OpenRouter |
OPENCLAW_CUSTOM_BASE_URL + OPENCLAW_CUSTOM_API_KEY |
One of two | Custom OpenAI-compatible API |
OPENCLAW_CUSTOM_MODEL_ID |
No | Explicit model id at the custom provider for the main model |
JUDGE_MODEL |
No | Judge model; default in .env.example |
JUDGE_CUSTOM_BASE_URL + JUDGE_CUSTOM_API_KEY |
No | Separate custom endpoint for the judge |
JUDGE_CUSTOM_MODEL_ID |
No | Explicit model id for the judge custom endpoint |
DOCKER_IMAGE |
No | Local image tag; must match the loaded image |
🔌 Custom OpenAI-compatible API
If you do not use OpenRouter, set in .env:
OPENCLAW_CUSTOM_BASE_URL=https://your-api-url/v1
OPENCLAW_CUSTOM_API_KEY=your_api_key
OPENCLAW_CUSTOM_MODEL_ID=your-provider/your-model
DEFAULT_MODEL=your-provider/your-model
If the API runs on the host:
OPENCLAW_CUSTOM_BASE_URL=http://host.docker.internal:8000/v1
When the judge uses a separate endpoint:
JUDGE_CUSTOM_BASE_URL=https://your-judge-api-url/v1
JUDGE_CUSTOM_API_KEY=your_judge_api_key
JUDGE_CUSTOM_MODEL_ID=your-provider/your-judge-model
Common Auth Setups (Main Model vs Judge)
| Scenario | Main model | Judge | Required config |
|---|---|---|---|
| A | Custom API | OpenRouter | OPENCLAW_CUSTOM_* + OPENROUTER_API_KEY |
| B | OpenRouter | OpenRouter | OPENROUTER_API_KEY |
| C | Custom API | Custom API (separate endpoint) | OPENCLAW_CUSTOM_* + JUDGE_CUSTOM_* |
5. Run Evaluation
# Run all tasks
python dataclaw/eval/run_batch.py --model openrouter/anthropic/claude-sonnet-4.6
# Run selected tasks
python dataclaw/eval/run_batch.py --model ... --suite task_001,task_002
# Run in parallel
python dataclaw/eval/run_batch.py --model ... --parallel 4
# Run a single task file
python dataclaw/eval/run_batch.py --task tasks/task_001_xxx.md
# Or use the convenience script (reads DEFAULT_MODEL from .env)
bash script/run.sh
CLI Options
| Flag | Default | Description |
|---|---|---|
--model / -m |
DEFAULT_MODEL in .env |
Model under test |
--judge |
JUDGE_MODEL in .env |
Judge model |
--suite / -s |
all |
"all" or comma-separated task IDs |
--task / -t |
— | Path to a single task.md |
--parallel / -p |
1 |
Parallel container count |
--timeout-multiplier |
1.0 |
Scale all task timeouts |
--runs |
1 |
Repeat runs per task |
--resume |
— | Resume from last interrupted run |
--verbose / -v |
— | Enable verbose logging |
6. Results
After a run completes, results are saved under output/<task_id>/<model_timestamp_runid>/:
output/<task_id>/<suffix>/
├── score.json # outcome score (Acc)
├── process_score.json # process scores (EE / GPR / TPE)
├── usage.json # token usage, cost, elapsed time
├── agent.log # agent execution log
├── gateway.log # gateway log
├── chat.jsonl # full conversation record
├── judge_chat.jsonl # outcome-judge conversation
└── judge_process_chat.jsonl # process-judge conversation
A global summary is written to:
output/summary_<model>.json
7. Grading Rules
DataClaw scores each run along four metrics.
| Metric | Definition | Scope | Direction |
|---|---|---|---|
| Acc | LLM-judge semantic match between predicted answer â and gold answer a; multi-subquestion tasks return the normalized mean over the L sub-answers. | All tasks | ↑ |
| EE | Execution Efficiency = N / T, where N is the gold reference step count and T is the agent's actual step count. EE > 1 means the agent solved it in fewer steps than the gold trajectory. | Correct tasks only | ↑ |
| GPR | Goal Progress Rate = (1/M) Σⱼ 𝕀(mⱼ achieved); fraction of M annotated milestones the agent reaches anywhere in its trajectory. Captures partial process credit when the final answer is wrong. | Incorrect tasks only | ↑ |
| TPE | Temporal Progress Efficiency = (Σⱼ 𝕀(mⱼ) · γ^max(tⱼ − N, 0)) / Σⱼ 𝕀(mⱼ), γ = 0.9; averages an exponential temporal-decay factor over the milestones the agent did achieve. Milestones reached by step N contribute 1; later ones decay. TPE = 1 means all achieved milestones were on time, lower values indicate later concentration. Range [0, 1]. | Incorrect tasks only | ↑ |
8. Resume After Interruption
Long batch evaluations may be interrupted unexpectedly. The evaluation framework automatically saves a progress file after each task completes:
output/progress_<model>.json
Simply append --resume to the original command to resume:
# Original run (interrupted midway)
python dataclaw/eval/run_batch.py --model openrouter/anthropic/claude-sonnet-4.6 --suite all
# Resume (keep other arguments the same)
python dataclaw/eval/run_batch.py --model openrouter/anthropic/claude-sonnet-4.6 --suite all --resume
On resume, the framework automatically verifies that --model, --suite, and --runs match the previous run; if they don't, it exits with an error. Once all tasks are completed, the progress file is removed automatically.
To discard previous progress and start fresh, simply delete the progress file:
rm output/progress_<model>.json
9. Cleanup
Interrupted runs may leave behind uncleaned containers. Clean them up as follows:
IMAGE=<your-docker-image-tag>
docker ps -a --filter "ancestor=${IMAGE}" -q | xargs -r docker rm -f
Preview containers that would be removed:
IMAGE=<your-docker-image-tag>
docker ps -a --filter "ancestor=${IMAGE}" --format "{{.Names}}\t{{.Status}}"
📊 Dataset Statistics
DataClaw's data does not come from synthetic samples or teaching examples; it is built on the publishing team's long-term, front-line data accumulation and industry insights from research on Chinese enterprises, industries, and policies. The current version is mainly based on data from 2022. After necessary de-identification, tasks are constructed to avoid model knowledge leakage as much as possible while preserving the information noise and data friction found in real business settings. Task authoring and annotation are conducted by a professional team from Lingnan College, Sun Yat-sen University, balancing academic rigor and practical usability.
🗂️ Data Environment Statistics
Under a theme-domain view and business-oriented taxonomy, the current data environment is organized into 3 theme domains: Enterprise, Industry, and Policy; subcategories cover enterprise profiles and regional profiles, enterprise core competitiveness, business operating status, regional/national industry statistics, policy releases, and full policy texts — closely aligned with real research and consulting workflows. The 3 theme domains contain 17 independent data sources (each data file counts as one source, all mounted under assets/database/): 17 are placed under theme subdirectories enterprise/, industry/, policy/; in addition, 1 root-level file, internal_metrics.csv, serves as an internal business-logic knowledge base and does not belong to any theme domain. Details below.
| Dimension | Value | Notes |
|---|---|---|
| Theme domains | 3 | Enterprise, Industry, Policy |
| Secondary themes | 7 | Enterprise ×3 (profiles, core competitiveness, business status), Industry ×2 (regional industry, national industry), Policy ×2 (release status, full text) |
| Total data sources | 17 | Injected into the container workspace at run time |
| Format | CSV | Primarily CSV; includes both structured fields and unstructured long-text content |
| Time span | Mainly concentrated in 2022 | Statistical periods vary across sources |
The 17 data sources by theme domain and secondary theme
| Theme domain | Secondary theme | Sources | Files |
|---|---|---|---|
| Enterprise | Enterprise profiles | 5 | enterprise/company_profile.csventerprise/company_profile_as.csventerprise/company_profile_eu.csventerprise/company_profile_na.csventerprise/company_profile_oc.csv |
| Enterprise | Core competitiveness | 1 | enterprise/company_core.csv |
| Enterprise | Business status | 3 | enterprise/company_operation_status.csventerprise/company_operation_status_detail.csventerprise/company_operation_yearly_status.csv |
| Industry | Regional industry | 3 | industry/regional_industry_status.csvindustry/regional_industry_status_detail.csvindustry/regional_industry_yearly_status.csv |
| Industry | National industry | 3 | industry/national_industry_status.csvindustry/national_industry_status_detail.csvindustry/national_industry_yearly_status.csv |
| Policy | Policy release status | 1 | policy/policy_release_status.csv |
| Policy | Full policy text | 1 | policy/policy_resource.csv |
At execution time, agents typically need to align entities across files, join across tables, normalize definitions, and perform aggregation calculations, rather than simply looking up values in a single file; when needed, they must also consult business conventions in
internal_metrics.csv. This is the core value of DataClaw for evaluating real-scenario data understanding and reasoning capabilities.
📋 Task Statistics
The current version contains 492 tasks across 7 categories, with an overall difficulty distribution of 131 easy / 286 medium / 75 hard.
| Category code | Meaning | Count | Difficulty split |
|---|---|---|---|
enterprise_industry_analysis |
Enterprise–industry analysis | 226 | easy 115 / medium 111 |
enterprise_industry_policy_analysis |
Enterprise–industry–policy linkage analysis | 76 | easy 10 / medium 66 |
comprehensive_decision |
Comprehensive decision | 70 | easy 6 / medium 45 / hard 19 |
international_comparison |
International comparison | 39 | medium 25 / hard 14 |
hypothesis_verification |
Hypothesis verification | 29 | medium 14 / hard 15 |
industry_planning |
Industry planning | 28 | medium 14 / hard 14 |
risk_assessment |
Risk assessment | 24 | medium 11 / hard 13 |
Except for the 39
international_comparisontasks, all others are explicitly restricted in the current task spec to use only./database/, with no web search.
🙏 Acknowledgements
DataClaw is jointly released by Prof. Chuan Chen's team at the School of Computer Science, Sun Yat-sen University, and the Southern Weekly Sci-Tech Power Research Center. We sincerely thank the Southern Weekly Sci-Tech Power Research Center for providing invaluable data and tremendous support.
This project also builds on excellent open-source agent ecosystems. We gratefully acknowledge:
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