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| User Message,Expected Output,Acceptance Criteria | |
| How do I reverse a list in Python?,Use the `[::-1]` slicing technique or the `list.reverse()` method.,"Similar in meaning, text length and style." | |
| (2+8)*3,"(2+8)*3 | |
| = 10*3 | |
| = 30 | |
| "," | |
| * Exactly text match. | |
| * Acceptable differences: | |
| * Extra or missing spaces. | |
| * Extra or missing line breaks at the beginning or end of the output. | |
| " | |
| "Here is the GDP data in billions of US dollars (USD) for these years: | |
| Germany: | |
| 2015: $3,368.29 billion | |
| 2016: $3,467.79 billion | |
| 2017: $3,677.83 billion | |
| 2018: $3,946.00 billion | |
| 2019: $3,845.03 billion | |
| France: | |
| 2015: $2,423.47 billion | |
| 2016: $2,465.12 billion | |
| 2017: $2,582.49 billion | |
| 2018: $2,787.86 billion | |
| 2019: $2,715.52 billion | |
| United Kingdom: | |
| 2015: $2,860.58 billion | |
| 2016: $2,650.90 billion | |
| 2017: $2,622.43 billion | |
| 2018: $2,828.87 billion | |
| 2019: $2,829.21 billion | |
| Italy: | |
| 2015: $1,815.72 billion | |
| 2016: $1,852.50 billion | |
| 2017: $1,937.80 billion | |
| 2018: $2,073.90 billion | |
| 2019: $1,988.14 billion | |
| Spain: | |
| 2015: $1,199.74 billion | |
| 2016: $1,235.95 billion | |
| 2017: $1,313.13 billion | |
| 2018: $1,426.19 billion | |
| 2019: $1,430.38 billion | |
| ","Year,Germany,France,United Kingdom,Italy,Spain | |
| 2016-2015,2.96%,1.71%,-7.35%,2.02%,3.04% | |
| 2017-2016,5.08%,4.78%,-1.07%,4.61%,6.23% | |
| 2018-2017,7.48%,7.99%,7.89%,7.10%,8.58% | |
| 2019-2018,-2.56%,-2.59%,0.01%,-4.11%,0.30% | |
| "," | |
| * Strict text matching of the header row and first column(year). | |
| * Acceptable differences: | |
| * Differences in digital/percentage values in the table, even significant ones. | |
| * Extra or missing spaces. | |
| * Extra or missing line breaks. | |
| " | |
| "Gene sequence: ATGGCCATGGCGCCCAGAACTGAGATCAATAGTACCCGTATTAACGGGTGA | |
| Species: Escherichia coli","{ | |
| ""Gene Sequence Analysis Results"": { | |
| ""Basic Information"": { | |
| ""Sequence Length"": 54, | |
| ""GC Content"": ""51.85%"" | |
| }, | |
| ""Nucleotide Composition"": { | |
| ""A"": {""Count"": 12, ""Percentage"": ""22.22%""}, | |
| ""T"": {""Count"": 11, ""Percentage"": ""20.37%""}, | |
| ""G"": {""Count"": 16, ""Percentage"": ""29.63%""}, | |
| ""C"": {""Count"": 15, ""Percentage"": ""27.78%""} | |
| }, | |
| ""Codon Analysis"": { | |
| ""Start Codon"": ""ATG"", | |
| ""Stop Codon"": ""TGA"", | |
| ""Codon Table"": [ | |
| {""Codon"": ""ATG"", ""Amino Acid"": ""Methionine"", ""Position"": 1}, | |
| {""Codon"": ""GCC"", ""Amino Acid"": ""Alanine"", ""Position"": 2}, | |
| {""Codon"": ""ATG"", ""Amino Acid"": ""Methionine"", ""Position"": 3}, | |
| // ... other codons ... | |
| {""Codon"": ""TGA"", ""Amino Acid"": ""Stop Codon"", ""Position"": 18} | |
| ] | |
| }, | |
| ""Potential Function Prediction"": { | |
| ""Protein Length"": 17, | |
| ""Possible Functional Domains"": [ | |
| {""Domain Name"": ""ABC Transporter"", ""Start Position"": 5, ""End Position"": 15, ""Confidence"": ""75%""}, | |
| {""Domain Name"": ""Membrane Protein"", ""Start Position"": 1, ""End Position"": 17, ""Confidence"": ""60%""} | |
| ], | |
| ""Secondary Structure Prediction"": { | |
| ""α-helix"": [""2-8"", ""12-16""], | |
| ""β-sheet"": [""9-11""], | |
| ""Random Coil"": [""1"", ""17""] | |
| } | |
| }, | |
| ""Homology Analysis"": { | |
| ""Most Similar Sequences"": [ | |
| { | |
| ""Gene Name"": ""abcT"", | |
| ""Species"": ""Salmonella enterica"", | |
| ""Similarity"": ""89%"", | |
| ""E-value"": ""3e-25"" | |
| }, | |
| { | |
| ""Gene Name"": ""yojI"", | |
| ""Species"": ""Escherichia coli"", | |
| ""Similarity"": ""95%"", | |
| ""E-value"": ""1e-30"" | |
| } | |
| ] | |
| }, | |
| ""Mutation Analysis"": { | |
| ""SNP Sites"": [ | |
| {""Position"": 27, ""Wild Type"": ""A"", ""Mutant"": ""G"", ""Amino Acid Change"": ""Glutamine->Arginine""}, | |
| {""Position"": 42, ""Wild Type"": ""C"", ""Mutant"": ""T"", ""Amino Acid Change"": ""None (Synonymous Mutation)""} | |
| ] | |
| } | |
| } | |
| }","* Consistent with Expected Output: | |
| * Formats of all JSON sections | |
| * Data types of all JSON fields | |
| * Top layer sections | |
| * Acceptable differences: | |
| * Extra or missing spaces | |
| * Extra or missing line breaks at the beginning or end of the output | |
| * Differences in JSON field values | |
| * JSON wrapped in backquotes" | |
| 今天下午3点，在北京国家会议中心，阿里巴巴集团董事局主席马云宣布将投资100亿元人民币用于农村电商发展。这一决定受到了与会代表的热烈欢迎，大家认为这将为中国农村经济带来新的机遇。,"{ | |
| ""文本分析结果"": { | |
| ""情感分析"": { | |
| ""整体情感"": ""积极"", | |
| ""情感得分"": 0.82, | |
| ""情感细分"": { | |
| ""乐观"": 0.75, | |
| ""兴奋"": 0.60, | |
| ""期待"": 0.85 | |
| } | |
| }, | |
| ""实体识别"": [ | |
| {""实体"": ""北京"", ""类型"": ""地点"", ""起始位置"": 7, ""结束位置"": 9}, | |
| {""实体"": ""国家会议中心"", ""类型"": ""地点"", ""起始位置"": 9, ""结束位置"": 15}, | |
| {""实体"": ""阿里巴巴集团"", ""类型"": ""组织"", ""起始位置"": 16, ""结束位置"": 22}, | |
| {""实体"": ""马云"", ""类型"": ""人物"", ""起始位置"": 26, ""结束位置"": 28}, | |
| {""实体"": ""100亿元"", ""类型"": ""金额"", ""起始位置"": 32, ""结束位置"": 37}, | |
| {""实体"": ""人民币"", ""类型"": ""货币"", ""起始位置"": 37, ""结束位置"": 40}, | |
| {""实体"": ""中国"", ""类型"": ""地点"", ""起始位置"": 71, ""结束位置"": 73} | |
| ], | |
| ""关键词提取"": [ | |
| {""关键词"": ""农村电商"", ""权重"": 0.95}, | |
| {""关键词"": ""马云"", ""权重"": 0.85}, | |
| {""关键词"": ""投资"", ""权重"": 0.80}, | |
| {""关键词"": ""阿里巴巴"", ""权重"": 0.75}, | |
| {""关键词"": ""经济机遇"", ""权重"": 0.70} | |
| ] | |
| } | |
| }","* Consistent with Expected Output: | |
| * Formats of all JSON sections | |
| * Data types of all JSON fields | |
| * Top layer sections | |
| * Acceptable differences: | |
| * Differences in digital values in the table. | |
| * Extra or missing spaces. | |
| * Extra or missing line breaks at the beginning or end of the output. | |
| * Differences in JSON field values | |
| * Differences in section/item orders. | |
| * JSON wrapped in backquotes." | |
| Low-noise amplifier,"A '''low-noise amplifier''' ('''LNA''') is an electronic component that amplifies a very low-power [[signal]] without significantly degrading its [[signal-to-noise ratio]] (SNR). Any [[electronic amplifier]] will increase the power of both the signal and the [[Noise (electronics)|noise]] present at its input, but the amplifier will also introduce some additional noise. LNAs are designed to minimize that additional noise, by choosing special components, operating points, and [[Circuit topology (electrical)|circuit topologies]]. Minimizing additional noise must balance with other design goals such as [[power gain]] and [[impedance matching]]. | |
| LNAs are found in [[Radio|radio communications]] systems, [[Amateur Radio]] stations, medical instruments and [[electronic test equipment]]. A typical LNA may supply a power gain of 100 (20 [[decibels]] (dB)) while decreasing the SNR by less than a factor of two (a 3 dB [[noise figure]] (NF)). Although LNAs are primarily concerned with weak signals that are just above the [[noise floor]], they must also consider the presence of larger signals that cause [[intermodulation distortion]].","* Consistent with Expected Output: | |
| * Language | |
| * Text length | |
| * Text style | |
| * Text structures | |
| * Cover all the major content of Expected Output. | |
| * Acceptable differences: | |
| * Minor format differences. | |
| * Expression differences. | |
| * Numerical differences. | |
| * Additional content in Actual Output. | |
| * Missing minor content in Actual Output." | |
| What is the meaning of life?,"[ | |
| {""persona"": ""Philosopher"", ""prompt"": ""Explore the concept of life's meaning through the lens of existentialism and purpose-driven existence.""}, | |
| {""persona"": ""Scientist"", ""prompt"": ""Examine the biological and evolutionary perspectives on the function and significance of life.""}, | |
| {""persona"": ""Child"", ""prompt"": ""Imagine you're explaining to a curious 7-year-old what makes life special and important.""} | |
| ]","* Consistent with Expected Output: | |
| * Formats of all JSON sections | |
| * Data types and formats of all JSON fields | |
| * Top layer sections | |
| * Acceptable differences: | |
| * Differences in field values | |
| * Extra or missing spaces | |
| * Extra or missing line breaks at the beginning or end of the output | |
| * JSON wrapped in backquotes" | |
| "<?php | |
| $username = $_POST['username']; | |
| $password = $_POST['password']; | |
| $query = ""SELECT * FROM users WHERE username = '$username' AND password = '$password'""; | |
| $result = mysqli_query($connection, $query); | |
| if (mysqli_num_rows($result) > 0) { | |
| echo ""Login successful""; | |
| } else { | |
| echo ""Login failed""; | |
| } | |
| ?>","security_analysis: | |
| vulnerabilities: | |
| - type: SQL Injection | |
| severity: Critical | |
| description: Unsanitized user input directly used in SQL query | |
| mitigation: Use prepared statements or parameterized queries | |
| - type: Password Storage | |
| severity: High | |
| description: Passwords stored in plain text | |
| mitigation: Use password hashing (e.g., bcrypt) before storage | |
| additional_issues: | |
| - Lack of input validation | |
| - No CSRF protection | |
| - Potential for timing attacks in login logic | |
| overall_risk_score: 9.5/10 | |
| recommended_actions: | |
| - Implement proper input sanitization | |
| - Use secure password hashing algorithms | |
| - Add CSRF tokens to forms | |
| - Consider using a secure authentication library","* Consistent with Expected Output: | |
| * Formats of all YAML sections | |
| * Data types and formats of all YAML fields | |
| * Top layer sections | |
| * Acceptable differences: | |
| * Differences in field values | |
| * Extra or missing spaces | |
| * Extra or missing line breaks at the beginning or end of the output | |
| * YAML wrapped in backquotes" | |