ortiz-ai/qwen3-4b-structured-output-lora01_1_3e1_hardmarge
Text Generation
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Updated
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16
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string | messages
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daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following toml into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nTOML:\n[[items]]\nalphaAurora = 7933\nalpha_velox = 9544\natlas_beta = \"Gamma\"\natlas_ember = false\nbetaOmega = 7317.1\nlumen_lumen = false\nomega_ember = 9228\ntags = [\"beta\", \"eon\", \"alpha\", \"delta\"]\n[items.dimensions]\ndepth_cm = 74.6\nheight_cm = 249.0\nwidth_cm = 190.4\n[[items]]\nalpha_aurora = \"terra\"\nember_ember = \"gamma\"\neon_zephyr = 6479\nnotes = \"Atlas\"\nomega_beta = \"gamma\"\nterra_aurora = 7286.2\nzephyr_omega = \"Velox\"\ntags = [\"omega\", \"ember\", \"gamma\"]\n[items.dimensions]\ndepth_cm = 31.8\nheight_cm = 293.4\nwidth_cm = 240.9\n[items.flags]\narchived = true\nfeatured = false\n[[items]]\nemberEmber = \"Atlas\"\ngammaLumen = 985\ngamma_nova = true\nlumen_gamma = false\nlumen_terra = true\nterraGamma = \"Ember\"\nzephyrEon = 1465\ntags = [\"terra\", \"aurora\"]\n[items.dimensions]\ndepth_cm = 7.9\nheight_cm = 266.0\nwidth_cm = 203.4\n[items.flags]\narchived = false\nfeatured = false\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Nova\"\n[[items.meta]]\nkey = \"year\"\nvalue = 1953\n[[items]]\natlasAlpha = \"\"\neonOmega = \"eon\"\nnotes = \"Terra\"\nnovaBeta = false\nomega_delta = 4566\nzephyrBeta = 8218\ntags = [\"alpha\", \"velox\", \"atlas\"]\n[items.dimensions]\ndepth_cm = 31.5\nheight_cm = 270.2\nwidth_cm = 37.9\n[items.flags]\narchived = true\nfeatured = true\n[[items.components]]\nname = \"Eon\"\nqty = 5\n[[items.components]]\nname = \"Zephyr\"\nqty = 5\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Aurora\"\n[[items.meta]]\nkey = \"year\"\nvalue = 1965\n[[items]]\nalpha_atlas = \"\"\natlasBeta = false\nbeta_beta = 1927\ngamma_alpha = 1171.68\ngamma_delta = \"Ember\"\nomega_alpha = \"Gamma\"\nomega_zephyr = false\nvelox_aurora = 9817.01\nvelox_lumen = 9555.14\ntags = [\"velox\", \"beta\", \"alpha\"]\n[items.dimensions]\ndepth_cm = 18.7\nheight_cm = 91.6\nwidth_cm = 293.0\n[items.flags]\narchived = false\nfeatured = false\n[[items.components]]\nname = \"Atlas\"\nqty = 4\n[[items.components]]\nname = \"Aurora\"\nqty = 4\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Zephyr\"\n[[items.meta]]\nkey = \"year\"\nvalue = 1975",
"role": "user"
},
{
"content": "items:\n- alphaAurora: 7933\n atlas_beta: Gamma\n alpha_velox: 9544\n lumen_lumen: false\n betaOmega: 7317.1\n atlas_ember: false\n omega_ember: 9228\n dimensions:\n height_cm: 249.0\n width_cm: 190.4\n depth_cm: 74.6\n tags:\n - beta\n - eon\n - alpha\n - delta\n- alpha_aurora: terra\n ember_ember: gamma\n terra_aurora: 7286.2\n omega_beta: gamma\n eon_zephyr: 6479\n zephyr_omega: Velox\n dimensions:\n height_cm: 293.4\n width_cm: 240.9\n depth_cm: 31.8\n flags:\n featured: false\n archived: true\n tags:\n - omega\n - ember\n - gamma\n notes: Atlas\n- zephyrEon: 1465\n terraGamma: Ember\n gammaLumen: 985\n gamma_nova: true\n emberEmber: Atlas\n lumen_gamma: false\n lumen_terra: true\n dimensions:\n height_cm: 266.0\n width_cm: 203.4\n depth_cm: 7.9\n flags:\n featured: false\n archived: false\n tags:\n - terra\n - aurora\n meta:\n - key: origin\n value: Nova\n - key: year\n value: 1953\n- eonOmega: eon\n zephyrBeta: 8218\n novaBeta: false\n omega_delta: 4566\n atlasAlpha: ''\n dimensions:\n height_cm: 270.2\n width_cm: 37.9\n depth_cm: 31.5\n flags:\n featured: true\n archived: true\n tags:\n - alpha\n - velox\n - atlas\n meta:\n - key: origin\n value: Aurora\n - key: year\n value: 1965\n components:\n - name: Eon\n qty: 5\n - name: Zephyr\n qty: 5\n notes: Terra\n- atlasBeta: false\n beta_beta: 1927\n alpha_atlas: ''\n velox_lumen: 9555.14\n gamma_delta: Ember\n velox_aurora: 9817.01\n omega_alpha: Gamma\n omega_zephyr: false\n gamma_alpha: 1171.68\n dimensions:\n height_cm: 91.6\n width_cm: 293.0\n depth_cm: 18.7\n flags:\n featured: false\n archived: false\n tags:\n - velox\n - beta\n - alpha\n meta:\n - key: origin\n value: Zephyr\n - key: year\n value: 1975\n components:\n - name: Atlas\n qty: 4\n - name: Aurora\n qty: 4",
"role": "assistant"
}
] |
merged_dedup_00000
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daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output CSV.\nReturn ONLY CSV.\nATTRIBUTES:\nauroraVelox, novaOmega, aurora_alpha, omegaGamma, betaVelox, dimensions\nTEXT:\nauroraVelox: Nova | novaOmega: False | aurora_alpha: 3485 | omegaGamma: Alpha | betaVelox: 6975.45 | dimensions: {'height_cm': 250.0, 'width_cm': 170.2, 'depth_cm': 26.3}",
"role": "user"
},
{
"content": "auroraVelox,aurora_alpha,betaVelox,dimensions,novaOmega,omegaGamma\nNova,3485,6975.45,\"{\"\"height_cm\"\": 250.0, \"\"width_cm\"\": 170.2, \"\"depth_cm\"\": 26.3}\",false,Alpha",
"role": "assistant"
}
] |
merged_dedup_00001
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Reformat the TOML below into YAML:\nuser = \"boyersylvia\"\npost = \"Interview knowledge ready hold establish hotel several. Money subject away without special. Oil whether short air become.\"\nlikes = 450",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nuser: boyersylvia\npost: Interview knowledge ready hold establish hotel several. Money subject away without\n special. Oil whether short air become.\nlikes: 450",
"role": "assistant"
}
] |
merged_dedup_00002
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.archived, dimensions.height_cm, tags[1], tags[0], atlasDelta, veloxEon, betaAtlas, omega_velox\nTEXT:\nflags.archived: False | dimensions.height_cm: 105.9 | tags[1]: eon | tags[0]: eon | atlasDelta: 5465.44 | veloxEon: nova | betaAtlas: 7753.45 | omega_velox: ember",
"role": "user"
},
{
"content": "atlasDelta = 5465.44\nbetaAtlas = 7753.45\nomega_velox = \"ember\"\nveloxEon = \"nova\"\ntags = [\"eon\", \"eon\"]\n[dimensions]\nheight_cm = 105.9\n[flags]\narchived = false",
"role": "assistant"
}
] |
merged_dedup_00003
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ndimensions.height_cm, flags.archived, flags.featured, dimensions.depth_cm, auroraAlpha, veloxOmega, ember_nova, atlasZephyr\nTEXT:\ndimensions.height_cm: 241.1 | flags.archived: False | flags.featured: False | dimensions.depth_cm: 3.3 | auroraAlpha: | veloxOmega: Omega | ember_nova: 4779 | atlasZephyr: Beta",
"role": "user"
},
{
"content": "atlasZephyr = \"Beta\"\nauroraAlpha = \"\"\nember_nova = 4779\nveloxOmega = \"Omega\"\n[dimensions]\ndepth_cm = 3.3\nheight_cm = 241.1\n[flags]\narchived = false\nfeatured = false",
"role": "assistant"
}
] |
merged_dedup_00004
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\ntags[0], dimensions.depth_cm, dimensions.width_cm, dimensions.height_cm, lumen_lumen, terra_gamma, beta_eon, auroraAtlas\nTEXT:\ntags[0]: atlas | dimensions.depth_cm: 96.6 | dimensions.width_cm: 175.9 | dimensions.height_cm: 222.0 | lumen_lumen: False | terra_gamma: 9994.02 | beta_eon: | auroraAtlas: False",
"role": "user"
},
{
"content": "tags:\n- atlas\ndimensions:\n depth_cm: 96.6\n width_cm: 175.9\n height_cm: 222.0\nlumen_lumen: false\nterra_gamma: 9994.02\nbeta_eon: ''\nauroraAtlas: false",
"role": "assistant"
}
] |
merged_dedup_00005
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ndimensions.width_cm, dimensions.depth_cm, tags[0], dimensions.height_cm, aurora_gamma, deltaBeta, emberNova, auroraAtlas\nTEXT:\ndimensions.width_cm: 86.4 | dimensions.depth_cm: 41.3 | tags[0]: zephyr | dimensions.height_cm: 34.2 | aurora_gamma: zephyr | deltaBeta: beta | emberNova: | auroraAtlas: alpha",
"role": "user"
},
{
"content": "auroraAtlas = \"alpha\"\naurora_gamma = \"zephyr\"\ndeltaBeta = \"beta\"\nemberNova = \"\"\ntags = [\"zephyr\"]\n[dimensions]\ndepth_cm = 41.3\nheight_cm = 34.2\nwidth_cm = 86.4",
"role": "assistant"
}
] |
merged_dedup_00006
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.featured, flags.archived, dimensions.width_cm, dimensions.depth_cm, gammaTerra, gammaAurora, gamma_velox, omega_velox\nTEXT:\nflags.featured: False | flags.archived: True | dimensions.width_cm: 215.6 | dimensions.depth_cm: 34.9 | gammaTerra: | gammaAurora: 7744 | gamma_velox: False | omega_velox: 9913.98",
"role": "user"
},
{
"content": "gammaAurora = 7744\ngammaTerra = \"\"\ngamma_velox = false\nomega_velox = 9913.98\n[dimensions]\ndepth_cm = 34.9\nwidth_cm = 215.6\n[flags]\narchived = true\nfeatured = false",
"role": "assistant"
}
] |
merged_dedup_00007
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Convert the following XML into YAML.\nConstraints:\n- Preserve original tag names exactly (no renaming to snake_case).\n- Child elements become mapping keys; repeated elements become lists.\n- Keep ordering and nesting as in XML.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nXML:\n<root><items><velox_velox /><omegaAtlas>1596.64</omegaAtlas><velox_ember>426</velox_ember><lumenAlpha>aurora</lumenAlpha><delta_zephyr>Terra</delta_zephyr><gammaBeta>2227.19</gammaBeta><emberBeta>Terra</emberBeta><eon_atlas>delta</eon_atlas><terraBeta>false</terraBeta><dimensions><height_cm>153.8</height_cm><width_cm>60.8</width_cm><depth_cm>83.3</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><tags>alpha</tags><tags>omega</tags><tags>ember</tags></items><items><zephyr_atlas>6494</zephyr_atlas><ember_aurora>1110.17</ember_aurora><gamma_atlas>4985</gamma_atlas><eon_zephyr>4580</eon_zephyr><eonLumen>true</eonLumen><dimensions><height_cm>274.3</height_cm><width_cm>294.6</width_cm><depth_cm>92.3</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>omega</tags><tags>eon</tags><meta><key>origin</key><value>Gamma</value></meta><meta><key>year</key><value>1903</value></meta></items><items><deltaBeta>true</deltaBeta><zephyr_aurora>6808</zephyr_aurora><atlas_beta /><veloxOmega>false</veloxOmega><terra_aurora>Atlas</terra_aurora><alpha_aurora>2363</alpha_aurora><ember_lumen>eon</ember_lumen><dimensions><height_cm>90.2</height_cm><width_cm>55.9</width_cm><depth_cm>4.4</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>aurora</tags><tags>aurora</tags><tags>ember</tags><tags>atlas</tags><components><name>Zephyr</name><qty>2</qty></components><components><name>Ember</name><qty>2</qty></components></items><items><emberBeta>ember</emberBeta><gamma_delta>omega</gamma_delta><zephyrAtlas /><veloxVelox>atlas</veloxVelox><alphaTerra>true</alphaTerra><dimensions><height_cm>10.8</height_cm><width_cm>234.5</width_cm><depth_cm>23.3</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><meta><key>origin</key><value>Velox</value></meta><meta><key>year</key><value>1934</value></meta></items></root>",
"role": "user"
},
{
"content": "items:\n- velox_velox: ''\n omegaAtlas: 1596.64\n velox_ember: 426\n lumenAlpha: aurora\n delta_zephyr: Terra\n gammaBeta: 2227.19\n emberBeta: Terra\n eon_atlas: delta\n terraBeta: false\n dimensions:\n height_cm: 153.8\n width_cm: 60.8\n depth_cm: 83.3\n flags:\n featured: false\n archived: false\n tags:\n - alpha\n - omega\n - ember\n- zephyr_atlas: 6494\n ember_aurora: 1110.17\n gamma_atlas: 4985\n eon_zephyr: 4580\n eonLumen: true\n dimensions:\n height_cm: 274.3\n width_cm: 294.6\n depth_cm: 92.3\n flags:\n featured: true\n archived: true\n tags:\n - omega\n - eon\n meta:\n - key: origin\n value: Gamma\n - key: year\n value: 1903\n- deltaBeta: true\n zephyr_aurora: 6808\n atlas_beta: ''\n veloxOmega: false\n terra_aurora: Atlas\n alpha_aurora: 2363\n ember_lumen: eon\n dimensions:\n height_cm: 90.2\n width_cm: 55.9\n depth_cm: 4.4\n flags:\n featured: true\n archived: true\n tags:\n - aurora\n - aurora\n - ember\n - atlas\n components:\n - name: Zephyr\n qty: 2\n - name: Ember\n qty: 2\n- emberBeta: ember\n gamma_delta: omega\n zephyrAtlas: ''\n veloxVelox: atlas\n alphaTerra: true\n dimensions:\n height_cm: 10.8\n width_cm: 234.5\n depth_cm: 23.3\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Velox\n - key: year\n value: 1934",
"role": "assistant"
}
] |
merged_dedup_00008
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following JSON into well-formed XML.\nConstraints:\n- Use child elements only (no XML attributes).\n- Preserve key names and their letter case exactly.\n- Represent lists by repeating child elements in order.\nReturn ONLY XML.\nJSON:\n{\"items\": [{\"emberNova\": \"Gamma\", \"deltaAlpha\": \"Aurora\", \"eonOmega\": \"nova\", \"deltaDelta\": \"Ember\", \"terra_beta\": \"\", \"omegaAurora\": 218.53, \"dimensions\": {\"height_cm\": 163.6, \"width_cm\": 106.4, \"depth_cm\": 99.6}, \"flags\": {\"featured\": false, \"archived\": false}, \"tags\": [\"zephyr\", \"omega\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Lumen\"}, {\"key\": \"year\", \"value\": 2024}], \"notes\": \"\"}, {\"zephyrZephyr\": true, \"aurora_terra\": \"lumen\", \"terra_gamma\": 4210.65, \"atlasBeta\": \"\", \"auroraZephyr\": 1385, \"terraTerra\": \"terra\", \"terra_beta\": \"Atlas\", \"dimensions\": {\"height_cm\": 293.0, \"width_cm\": 208.3, \"depth_cm\": 64.9}, \"flags\": {\"featured\": true, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Omega\"}, {\"key\": \"year\", \"value\": 1980}]}, {\"gammaAlpha\": \"ember\", \"omega_aurora\": \"Atlas\", \"omegaAurora\": \"Ember\", \"nova_atlas\": \"lumen\", \"alphaVelox\": \"Velox\", \"veloxAurora\": 1523, \"lumenZephyr\": \"Omega\", \"alpha_ember\": true, \"alpha_delta\": \"Gamma\", \"dimensions\": {\"height_cm\": 109.3, \"width_cm\": 50.9, \"depth_cm\": 16.6}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"lumen\", \"zephyr\"], \"notes\": \"\"}, {\"terra_aurora\": 2435, \"velox_eon\": \"delta\", \"aurora_alpha\": \"omega\", \"terraBeta\": 5606.5, \"velox_zephyr\": \"terra\", \"betaTerra\": 6759.6, \"atlas_delta\": \"terra\", \"terra_delta\": 4431, \"gammaEmber\": false, \"dimensions\": {\"height_cm\": 53.7, \"width_cm\": 271.1, \"depth_cm\": 19.3}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"ember\", \"eon\", \"nova\", \"nova\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Eon\"}, {\"key\": \"year\", \"value\": 1932}]}, {\"lumen_atlas\": 8287.11, \"aurora_terra\": \"terra\", \"omega_nova\": \"delta\", \"novaZephyr\": 3459, \"deltaTerra\": 8286.88, \"terra_delta\": 3740.14, \"gamma_aurora\": true, \"omega_omega\": \"atlas\", \"dimensions\": {\"height_cm\": 110.1, \"width_cm\": 160.3, \"depth_cm\": 20.4}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"omega\", \"terra\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Terra\"}, {\"key\": \"year\", \"value\": 1974}]}, {\"atlas_zephyr\": \"Zephyr\", \"atlasAtlas\": 1665.48, \"omega_gamma\": false, \"zephyrNova\": 373, \"eon_delta\": \"Velox\", \"atlas_eon\": false, \"dimensions\": {\"height_cm\": 128.9, \"width_cm\": 283.1, \"depth_cm\": 4.6}, \"flags\": {\"featured\": true, \"archived\": false}, \"tags\": [\"velox\", \"nova\", \"aurora\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Nova\"}, {\"key\": \"year\", \"value\": 1971}]}]}",
"role": "user"
},
{
"content": "<root><items><emberNova>Gamma</emberNova><deltaAlpha>Aurora</deltaAlpha><eonOmega>nova</eonOmega><deltaDelta>Ember</deltaDelta><terra_beta /><omegaAurora>218.53</omegaAurora><dimensions><height_cm>163.6</height_cm><width_cm>106.4</width_cm><depth_cm>99.6</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><tags>zephyr</tags><tags>omega</tags><meta><key>origin</key><value>Lumen</value></meta><meta><key>year</key><value>2024</value></meta><notes /></items><items><zephyrZephyr>true</zephyrZephyr><aurora_terra>lumen</aurora_terra><terra_gamma>4210.65</terra_gamma><atlasBeta /><auroraZephyr>1385</auroraZephyr><terraTerra>terra</terraTerra><terra_beta>Atlas</terra_beta><dimensions><height_cm>293.0</height_cm><width_cm>208.3</width_cm><depth_cm>64.9</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><meta><key>origin</key><value>Omega</value></meta><meta><key>year</key><value>1980</value></meta></items><items><gammaAlpha>ember</gammaAlpha><omega_aurora>Atlas</omega_aurora><omegaAurora>Ember</omegaAurora><nova_atlas>lumen</nova_atlas><alphaVelox>Velox</alphaVelox><veloxAurora>1523</veloxAurora><lumenZephyr>Omega</lumenZephyr><alpha_ember>true</alpha_ember><alpha_delta>Gamma</alpha_delta><dimensions><height_cm>109.3</height_cm><width_cm>50.9</width_cm><depth_cm>16.6</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>lumen</tags><tags>zephyr</tags><notes /></items><items><terra_aurora>2435</terra_aurora><velox_eon>delta</velox_eon><aurora_alpha>omega</aurora_alpha><terraBeta>5606.5</terraBeta><velox_zephyr>terra</velox_zephyr><betaTerra>6759.6</betaTerra><atlas_delta>terra</atlas_delta><terra_delta>4431</terra_delta><gammaEmber>false</gammaEmber><dimensions><height_cm>53.7</height_cm><width_cm>271.1</width_cm><depth_cm>19.3</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>ember</tags><tags>eon</tags><tags>nova</tags><tags>nova</tags><meta><key>origin</key><value>Eon</value></meta><meta><key>year</key><value>1932</value></meta></items><items><lumen_atlas>8287.11</lumen_atlas><aurora_terra>terra</aurora_terra><omega_nova>delta</omega_nova><novaZephyr>3459</novaZephyr><deltaTerra>8286.88</deltaTerra><terra_delta>3740.14</terra_delta><gamma_aurora>true</gamma_aurora><omega_omega>atlas</omega_omega><dimensions><height_cm>110.1</height_cm><width_cm>160.3</width_cm><depth_cm>20.4</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>omega</tags><tags>terra</tags><meta><key>origin</key><value>Terra</value></meta><meta><key>year</key><value>1974</value></meta></items><items><atlas_zephyr>Zephyr</atlas_zephyr><atlasAtlas>1665.48</atlasAtlas><omega_gamma>false</omega_gamma><zephyrNova>373</zephyrNova><eon_delta>Velox</eon_delta><atlas_eon>false</atlas_eon><dimensions><height_cm>128.9</height_cm><width_cm>283.1</width_cm><depth_cm>4.6</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>velox</tags><tags>nova</tags><tags>aurora</tags><meta><key>origin</key><value>Nova</value></meta><meta><key>year</key><value>1971</value></meta></items></root>",
"role": "assistant"
}
] |
merged_dedup_00009
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\nflags.archived, tags[1], dimensions.height_cm, dimensions.width_cm, omega_eon, beta_zephyr, aurora_terra, atlas_delta\nTEXT:\nflags.archived: True | tags[1]: eon | dimensions.height_cm: 194.6 | dimensions.width_cm: 56.1 | omega_eon: 275 | beta_zephyr: Terra | aurora_terra: atlas | atlas_delta: 7091",
"role": "user"
},
{
"content": "flags:\n archived: true\ntags:\n- ''\n- eon\ndimensions:\n height_cm: 194.6\n width_cm: 56.1\nomega_eon: 275\nbeta_zephyr: Terra\naurora_terra: atlas\natlas_delta: 7091",
"role": "assistant"
}
] |
merged_dedup_00010
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following JSON into well-formed XML.\nConstraints:\n- Use child elements only (no XML attributes).\n- Preserve key names and their letter case exactly.\n- Represent lists by repeating child elements in order.\nReturn ONLY XML.\nJSON:\n{\"items\": [{\"auroraAurora\": \"velox\", \"nova_terra\": \"Alpha\", \"alphaDelta\": 9538.05, \"beta_nova\": 2547, \"omega_gamma\": \"\", \"eonDelta\": true, \"alpha_beta\": 9236, \"dimensions\": {\"height_cm\": 59.1, \"width_cm\": 17.3, \"depth_cm\": 87.3}, \"flags\": {\"featured\": false, \"archived\": true}, \"tags\": [\"eon\", \"terra\", \"gamma\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Atlas\"}, {\"key\": \"year\", \"value\": 1941}]}, {\"eonAtlas\": \"Omega\", \"eon_eon\": \"alpha\", \"lumen_eon\": false, \"zephyrLumen\": 6797, \"novaGamma\": 6648, \"zephyrGamma\": \"\", \"emberAurora\": \"gamma\", \"dimensions\": {\"height_cm\": 21.0, \"width_cm\": 223.7, \"depth_cm\": 51.6}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"velox\", \"eon\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Beta\"}, {\"key\": \"year\", \"value\": 1987}], \"components\": [{\"name\": \"Eon\", \"qty\": 3}, {\"name\": \"Beta\", \"qty\": 2}]}, {\"omegaAurora\": 3478.58, \"omega_delta\": 6668, \"terra_terra\": \"zephyr\", \"emberNova\": 9056.34, \"auroraAlpha\": 1269.86, \"alpha_aurora\": \"zephyr\", \"dimensions\": {\"height_cm\": 18.6, \"width_cm\": 32.2, \"depth_cm\": 63.1}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"lumen\", \"lumen\", \"omega\", \"omega\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Terra\"}, {\"key\": \"year\", \"value\": 2015}], \"components\": [{\"name\": \"Zephyr\", \"qty\": 2}, {\"name\": \"Terra\", \"qty\": 2}]}]}",
"role": "user"
},
{
"content": "<root><items><auroraAurora>velox</auroraAurora><nova_terra>Alpha</nova_terra><alphaDelta>9538.05</alphaDelta><beta_nova>2547</beta_nova><omega_gamma /><eonDelta>true</eonDelta><alpha_beta>9236</alpha_beta><dimensions><height_cm>59.1</height_cm><width_cm>17.3</width_cm><depth_cm>87.3</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>eon</tags><tags>terra</tags><tags>gamma</tags><meta><key>origin</key><value>Atlas</value></meta><meta><key>year</key><value>1941</value></meta></items><items><eonAtlas>Omega</eonAtlas><eon_eon>alpha</eon_eon><lumen_eon>false</lumen_eon><zephyrLumen>6797</zephyrLumen><novaGamma>6648</novaGamma><zephyrGamma /><emberAurora>gamma</emberAurora><dimensions><height_cm>21.0</height_cm><width_cm>223.7</width_cm><depth_cm>51.6</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>velox</tags><tags>eon</tags><meta><key>origin</key><value>Beta</value></meta><meta><key>year</key><value>1987</value></meta><components><name>Eon</name><qty>3</qty></components><components><name>Beta</name><qty>2</qty></components></items><items><omegaAurora>3478.58</omegaAurora><omega_delta>6668</omega_delta><terra_terra>zephyr</terra_terra><emberNova>9056.34</emberNova><auroraAlpha>1269.86</auroraAlpha><alpha_aurora>zephyr</alpha_aurora><dimensions><height_cm>18.6</height_cm><width_cm>32.2</width_cm><depth_cm>63.1</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>lumen</tags><tags>lumen</tags><tags>omega</tags><tags>omega</tags><meta><key>origin</key><value>Terra</value></meta><meta><key>year</key><value>2015</value></meta><components><name>Zephyr</name><qty>2</qty></components><components><name>Terra</name><qty>2</qty></components></items></root>",
"role": "assistant"
}
] |
merged_dedup_00011
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following JSON into well-formed XML.\nConstraints:\n- Use child elements only (no XML attributes).\n- Preserve key names and their letter case exactly.\n- Represent lists by repeating child elements in order.\nReturn ONLY XML.\nJSON:\n{\"items\": [{\"velox_delta\": false, \"deltaEon\": 5836.02, \"gammaEmber\": false, \"omega_gamma\": \"nova\", \"terra_eon\": \"lumen\", \"components\": [{\"name\": \"Ember\", \"qty\": 5}, {\"name\": \"Omega\", \"qty\": 4}], \"notes\": \"\"}, {\"terra_aurora\": false, \"veloxOmega\": true, \"gamma_lumen\": 9777, \"novaOmega\": 765, \"nova_terra\": 7278.01, \"delta_aurora\": 7186.33, \"beta_aurora\": false, \"lumen_terra\": 4368, \"dimensions\": {\"height_cm\": 28.1, \"width_cm\": 227.9, \"depth_cm\": 77.4}, \"flags\": {\"featured\": true, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Eon\"}, {\"key\": \"year\", \"value\": 1914}]}, {\"emberAlpha\": true, \"eon_lumen\": 9909.29, \"gammaGamma\": false, \"ember_ember\": false, \"atlasLumen\": 6563, \"dimensions\": {\"height_cm\": 206.2, \"width_cm\": 158.9, \"depth_cm\": 32.9}, \"flags\": {\"featured\": false, \"archived\": false}, \"components\": [{\"name\": \"Beta\", \"qty\": 5}, {\"name\": \"Velox\", \"qty\": 5}]}]}",
"role": "user"
},
{
"content": "<root><items><velox_delta>false</velox_delta><deltaEon>5836.02</deltaEon><gammaEmber>false</gammaEmber><omega_gamma>nova</omega_gamma><terra_eon>lumen</terra_eon><components><name>Ember</name><qty>5</qty></components><components><name>Omega</name><qty>4</qty></components><notes /></items><items><terra_aurora>false</terra_aurora><veloxOmega>true</veloxOmega><gamma_lumen>9777</gamma_lumen><novaOmega>765</novaOmega><nova_terra>7278.01</nova_terra><delta_aurora>7186.33</delta_aurora><beta_aurora>false</beta_aurora><lumen_terra>4368</lumen_terra><dimensions><height_cm>28.1</height_cm><width_cm>227.9</width_cm><depth_cm>77.4</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><meta><key>origin</key><value>Eon</value></meta><meta><key>year</key><value>1914</value></meta></items><items><emberAlpha>true</emberAlpha><eon_lumen>9909.29</eon_lumen><gammaGamma>false</gammaGamma><ember_ember>false</ember_ember><atlasLumen>6563</atlasLumen><dimensions><height_cm>206.2</height_cm><width_cm>158.9</width_cm><depth_cm>32.9</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><components><name>Beta</name><qty>5</qty></components><components><name>Velox</name><qty>5</qty></components></items></root>",
"role": "assistant"
}
] |
merged_dedup_00012
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Convert the following JSON into well-formed XML.\nConstraints:\n- Use child elements only (no XML attributes).\n- Preserve key names and their letter case exactly.\n- Represent lists by repeating child elements in order.\nReturn ONLY XML.\nJSON:\n{\"items\": [{\"novaVelox\": 6860.7, \"velox_alpha\": true, \"auroraTerra\": \"Omega\", \"atlasTerra\": 1361.92, \"omegaEon\": false, \"omega_velox\": true, \"eon_omega\": 5405, \"gammaNova\": true, \"dimensions\": {\"height_cm\": 291.6, \"width_cm\": 284.5, \"depth_cm\": 34.6}, \"flags\": {\"featured\": true, \"archived\": false}, \"tags\": [\"nova\", \"velox\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Gamma\"}, {\"key\": \"year\", \"value\": 1948}]}, {\"lumen_aurora\": \"lumen\", \"delta_omega\": \"terra\", \"zephyrLumen\": true, \"nova_beta\": 9708.15, \"veloxEon\": 3870, \"omegaGamma\": 5891, \"emberGamma\": false, \"alpha_alpha\": 7963.51, \"nova_velox\": true, \"dimensions\": {\"height_cm\": 152.5, \"width_cm\": 30.5, \"depth_cm\": 62.9}, \"flags\": {\"featured\": true, \"archived\": false}, \"components\": [{\"name\": \"Gamma\", \"qty\": 4}, {\"name\": \"Beta\", \"qty\": 3}]}, {\"novaBeta\": 6152, \"gamma_nova\": \"\", \"eonGamma\": 1559, \"betaVelox\": \"\", \"aurora_ember\": 7693, \"atlasOmega\": \"\", \"velox_eon\": \"Delta\", \"dimensions\": {\"height_cm\": 155.5, \"width_cm\": 76.9, \"depth_cm\": 37.7}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"terra\", \"terra\", \"aurora\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Omega\"}, {\"key\": \"year\", \"value\": 1974}]}, {\"aurora_velox\": 4356.08, \"emberLumen\": 5092, \"nova_terra\": \"Alpha\", \"omega_gamma\": 9117, \"omega_lumen\": \"ember\", \"delta_delta\": \"Nova\", \"lumenAurora\": 5078.26, \"omegaEmber\": 5233.02, \"eon_nova\": 7419, \"dimensions\": {\"height_cm\": 8.3, \"width_cm\": 261.8, \"depth_cm\": 50.0}, \"flags\": {\"featured\": true, \"archived\": false}, \"tags\": [\"alpha\", \"velox\", \"terra\"], \"components\": [{\"name\": \"Nova\", \"qty\": 5}, {\"name\": \"Aurora\", \"qty\": 1}]}, {\"lumenBeta\": \"zephyr\", \"nova_eon\": 3635.51, \"lumenOmega\": \"Beta\", \"betaEon\": true, \"terraVelox\": 6304.43, \"zephyr_gamma\": \"beta\", \"dimensions\": {\"height_cm\": 34.6, \"width_cm\": 242.1, \"depth_cm\": 36.8}, \"tags\": [\"delta\", \"delta\"]}, {\"omega_gamma\": true, \"alpha_beta\": 6151, \"ember_terra\": \"Delta\", \"novaAlpha\": false, \"lumenDelta\": \"Atlas\", \"eonLumen\": \"omega\", \"terra_delta\": true, \"lumenEon\": 5112, \"eon_zephyr\": true, \"dimensions\": {\"height_cm\": 119.3, \"width_cm\": 38.2, \"depth_cm\": 96.4}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"omega\", \"atlas\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Terra\"}, {\"key\": \"year\", \"value\": 1931}], \"notes\": \"\"}]}",
"role": "user"
},
{
"content": "<root><items><novaVelox>6860.7</novaVelox><velox_alpha>true</velox_alpha><auroraTerra>Omega</auroraTerra><atlasTerra>1361.92</atlasTerra><omegaEon>false</omegaEon><omega_velox>true</omega_velox><eon_omega>5405</eon_omega><gammaNova>true</gammaNova><dimensions><height_cm>291.6</height_cm><width_cm>284.5</width_cm><depth_cm>34.6</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>nova</tags><tags>velox</tags><meta><key>origin</key><value>Gamma</value></meta><meta><key>year</key><value>1948</value></meta></items><items><lumen_aurora>lumen</lumen_aurora><delta_omega>terra</delta_omega><zephyrLumen>true</zephyrLumen><nova_beta>9708.15</nova_beta><veloxEon>3870</veloxEon><omegaGamma>5891</omegaGamma><emberGamma>false</emberGamma><alpha_alpha>7963.51</alpha_alpha><nova_velox>true</nova_velox><dimensions><height_cm>152.5</height_cm><width_cm>30.5</width_cm><depth_cm>62.9</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><components><name>Gamma</name><qty>4</qty></components><components><name>Beta</name><qty>3</qty></components></items><items><novaBeta>6152</novaBeta><gamma_nova /><eonGamma>1559</eonGamma><betaVelox /><aurora_ember>7693</aurora_ember><atlasOmega /><velox_eon>Delta</velox_eon><dimensions><height_cm>155.5</height_cm><width_cm>76.9</width_cm><depth_cm>37.7</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>terra</tags><tags>terra</tags><tags>aurora</tags><meta><key>origin</key><value>Omega</value></meta><meta><key>year</key><value>1974</value></meta></items><items><aurora_velox>4356.08</aurora_velox><emberLumen>5092</emberLumen><nova_terra>Alpha</nova_terra><omega_gamma>9117</omega_gamma><omega_lumen>ember</omega_lumen><delta_delta>Nova</delta_delta><lumenAurora>5078.26</lumenAurora><omegaEmber>5233.02</omegaEmber><eon_nova>7419</eon_nova><dimensions><height_cm>8.3</height_cm><width_cm>261.8</width_cm><depth_cm>50.0</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>alpha</tags><tags>velox</tags><tags>terra</tags><components><name>Nova</name><qty>5</qty></components><components><name>Aurora</name><qty>1</qty></components></items><items><lumenBeta>zephyr</lumenBeta><nova_eon>3635.51</nova_eon><lumenOmega>Beta</lumenOmega><betaEon>true</betaEon><terraVelox>6304.43</terraVelox><zephyr_gamma>beta</zephyr_gamma><dimensions><height_cm>34.6</height_cm><width_cm>242.1</width_cm><depth_cm>36.8</depth_cm></dimensions><tags>delta</tags><tags>delta</tags></items><items><omega_gamma>true</omega_gamma><alpha_beta>6151</alpha_beta><ember_terra>Delta</ember_terra><novaAlpha>false</novaAlpha><lumenDelta>Atlas</lumenDelta><eonLumen>omega</eonLumen><terra_delta>true</terra_delta><lumenEon>5112</lumenEon><eon_zephyr>true</eon_zephyr><dimensions><height_cm>119.3</height_cm><width_cm>38.2</width_cm><depth_cm>96.4</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>omega</tags><tags>atlas</tags><meta><key>origin</key><value>Terra</value></meta><meta><key>year</key><value>1931</value></meta><notes /></items></root>",
"role": "assistant"
}
] |
merged_dedup_00013
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\ntags[0], dimensions.depth_cm, flags.archived, tags[1], alpha_aurora, atlasVelox, deltaOmega, omegaAtlas\nTEXT:\ntags[0]: terra | dimensions.depth_cm: 44.5 | flags.archived: True | tags[1]: gamma | alpha_aurora: False | atlasVelox: False | deltaOmega: 5683.36 | omegaAtlas: 7028.88",
"role": "user"
},
{
"content": "tags:\n- terra\n- gamma\ndimensions:\n depth_cm: 44.5\nflags:\n archived: true\nalpha_aurora: false\natlasVelox: false\ndeltaOmega: 5683.36\nomegaAtlas: 7028.88",
"role": "assistant"
}
] |
merged_dedup_00014
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Reformat the TOML below into YAML:\ncourse = \"Sharable optimal workforce\"\nweeks = 10\ncredits = 3\n[[audit_log]]\naction = \"created\"\nby = \"alvaradomadison\"\ntimestamp = \"1979-10-24T16:32:42.906198\"\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:07.497018\"\nversion = \"v3.0\"\ntags = [ \"others\", \"teacher\", \"will\", \"attorney\", \"seek\",]",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (course, weeks, credits...) and a nesting depth of 3.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\ncourse: Sharable optimal workforce\nweeks: 10\ncredits: 3\nmeta_info:\n generated_at: '2026-01-22T04:03:07.497018'\n version: v3.0\n tags:\n - others\n - teacher\n - will\n - attorney\n - seek\naudit_log:\n- action: created\n by: alvaradomadison\n timestamp: '1979-10-24T16:32:42.906198'",
"role": "assistant"
}
] |
merged_dedup_00015
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Reformat the XML below into YAML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<error_log>\n<timestamp>2026-01-22T04:03:07.720466</timestamp>\n<level>ERROR</level>\n<message>Sign similar onto appear.</message>\n</error_log>",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\ntimestamp: '2026-01-22T04:03:07.720466'\nlevel: ERROR\nmessage: Sign similar onto appear.",
"role": "assistant"
}
] |
merged_dedup_00016
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.archived, tags[0], tags[1], flags.featured, alpha_beta, delta_beta, atlasVelox, terra_omega\nTEXT:\nflags.archived: True | tags[0]: alpha | tags[1]: lumen | flags.featured: True | alpha_beta: True | delta_beta: Terra | atlasVelox: 997 | terra_omega: 4037.95",
"role": "user"
},
{
"content": "alpha_beta = true\natlasVelox = 997\ndelta_beta = \"Terra\"\nterra_omega = 4037.95\ntags = [\"alpha\", \"lumen\"]\n[flags]\narchived = true\nfeatured = true",
"role": "assistant"
}
] |
merged_dedup_00017
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Convert the following XML to YAML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<financial_report>\n<company>Cox-Paul</company>\n<revenue>238284</revenue>\n<profit>88965</profit>\n</financial_report>",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (company, revenue, profit) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\ncompany: Cox-Paul\nrevenue: 238284\nprofit: 88965",
"role": "assistant"
}
] |
merged_dedup_00018
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML.",
"role": "system"
},
{
"content": "Transform this data from YAML to TOML:\nrx: b87c95fa-dcb8-4b86-abbc-2aad9a52b92e\ndrug: report\ndosage: 10mg",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (rx, drug, dosage) and a nesting depth of 1.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nrx = \"b87c95fa-dcb8-4b86-abbc-2aad9a52b92e\"\ndrug = \"report\"\ndosage = \"10mg\"",
"role": "assistant"
}
] |
merged_dedup_00019
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Convert the following XML into YAML.\nConstraints:\n- Preserve original tag names exactly (no renaming to snake_case).\n- Child elements become mapping keys; repeated elements become lists.\n- Keep ordering and nesting as in XML.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nXML:\n<root><items><eonVelox>false</eonVelox><gamma_lumen /><nova_gamma>2782</nova_gamma><beta_beta>Ember</beta_beta><beta_atlas>9368</beta_atlas><aurora_alpha>nova</aurora_alpha><gamma_ember>false</gamma_ember><ember_aurora>Delta</ember_aurora><ember_nova>Terra</ember_nova><dimensions><height_cm>184.7</height_cm><width_cm>259.0</width_cm><depth_cm>92.6</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>aurora</tags><tags>zephyr</tags><tags>eon</tags><tags>omega</tags><components><name>Nova</name><qty>4</qty></components><components><name>Beta</name><qty>4</qty></components><notes /></items><items><alphaEmber>2179.47</alphaEmber><delta_terra>ember</delta_terra><auroraAlpha>aurora</auroraAlpha><novaBeta>Eon</novaBeta><velox_zephyr>8086</velox_zephyr><terra_beta /><eon_aurora>6470</eon_aurora><emberAlpha /><dimensions><height_cm>147.6</height_cm><width_cm>37.1</width_cm><depth_cm>56.9</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>gamma</tags><tags>terra</tags><tags>velox</tags><tags>zephyr</tags><notes>Velox</notes></items><items><deltaAtlas>4785</deltaAtlas><gammaBeta>false</gammaBeta><emberOmega>delta</emberOmega><veloxBeta>8265.61</veloxBeta><lumenNova>5441</lumenNova><betaEmber>5099.35</betaEmber><deltaOmega>false</deltaOmega><dimensions><height_cm>186.2</height_cm><width_cm>57.0</width_cm><depth_cm>58.4</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>zephyr</tags><tags>beta</tags><tags>nova</tags><tags>ember</tags><meta><key>origin</key><value>Atlas</value></meta><meta><key>year</key><value>1988</value></meta><components><name>Aurora</name><qty>1</qty></components><components><name>Delta</name><qty>3</qty></components><notes>Lumen</notes></items></root>",
"role": "user"
},
{
"content": "items:\n- eonVelox: false\n gamma_lumen: ''\n nova_gamma: 2782\n beta_beta: Ember\n beta_atlas: 9368\n aurora_alpha: nova\n gamma_ember: false\n ember_aurora: Delta\n ember_nova: Terra\n dimensions:\n height_cm: 184.7\n width_cm: 259.0\n depth_cm: 92.6\n flags:\n featured: false\n archived: true\n tags:\n - aurora\n - zephyr\n - eon\n - omega\n components:\n - name: Nova\n qty: 4\n - name: Beta\n qty: 4\n notes: ''\n- alphaEmber: 2179.47\n delta_terra: ember\n auroraAlpha: aurora\n novaBeta: Eon\n velox_zephyr: 8086\n terra_beta: ''\n eon_aurora: 6470\n emberAlpha: ''\n dimensions:\n height_cm: 147.6\n width_cm: 37.1\n depth_cm: 56.9\n flags:\n featured: true\n archived: true\n tags:\n - gamma\n - terra\n - velox\n - zephyr\n notes: Velox\n- deltaAtlas: 4785\n gammaBeta: false\n emberOmega: delta\n veloxBeta: 8265.61\n lumenNova: 5441\n betaEmber: 5099.35\n deltaOmega: false\n dimensions:\n height_cm: 186.2\n width_cm: 57.0\n depth_cm: 58.4\n flags:\n featured: false\n archived: true\n tags:\n - zephyr\n - beta\n - nova\n - ember\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 1988\n components:\n - name: Aurora\n qty: 1\n - name: Delta\n qty: 3\n notes: Lumen",
"role": "assistant"
}
] |
merged_dedup_00020
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\ndimensions.height_cm, dimensions.depth_cm, dimensions.width_cm, atlasEmber, lumenAlpha, notes, emberZephyr, ember_terra\nTEXT:\ndimensions.height_cm: 138.0 | dimensions.depth_cm: 70.2 | dimensions.width_cm: 126.9 | atlasEmber: 3623 | lumenAlpha: | notes: Eon | emberZephyr: eon | ember_terra: 7498.94",
"role": "user"
},
{
"content": "dimensions:\n height_cm: 138.0\n depth_cm: 70.2\n width_cm: 126.9\natlasEmber: 3623\nlumenAlpha: ''\nnotes: Eon\nemberZephyr: eon\nember_terra: 7498.94",
"role": "assistant"
}
] |
merged_dedup_00021
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Transform this data from XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<financial_report>\n<company>Michael LLC</company>\n<revenue>205877</revenue>\n<profit>47434</profit>\n</financial_report>",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (company, revenue, profit) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\ncompany,revenue,profit\nMichael LLC,205877,47434",
"role": "assistant"
}
] |
merged_dedup_00022
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML.",
"role": "system"
},
{
"content": "Transform this data from CSV to XML:\nid,test,value,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\nf6914fa8-5977-4b0d-b0d9-169909ca61a6,change,75.6296920805981,2026-01-22T04:03:06.479900,v1.0,\"[\"\"onto\"\", \"\"goal\"\", \"\"Democrat\"\", \"\"have\"\", \"\"very\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"jillcarter\"\", \"\"timestamp\"\": \"\"1991-12-17T04:52:01.346405\"\"}]\"",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input CSV structure: It represents a dictionary with 5 root fields (id, test, value...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<lab_result>\n<id>f6914fa8-5977-4b0d-b0d9-169909ca61a6</id>\n<test>change</test>\n<value>75.6296920805981</value>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.479900</generated_at>\n<version>v1.0</version>\n<tags>onto</tags>\n<tags>goal</tags>\n<tags>Democrat</tags>\n<tags>have</tags>\n<tags>very</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>jillcarter</by>\n<timestamp>1991-12-17T04:52:01.346405</timestamp>\n</audit_log>\n</lab_result>",
"role": "assistant"
}
] |
merged_dedup_00023
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML.",
"role": "system"
},
{
"content": "Transform this data from XML to TOML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<social_media_post>\n<user>fcortez</user>\n<post>Before two exactly last save affect. Why major challenge strong gas far yard.</post>\n<likes>176</likes>\n<meta_info>\n<generated_at>2026-01-22T04:03:06.579863</generated_at>\n<version>v1.0</version>\n<tags>deal</tags>\n<tags>heart</tags>\n<tags>value</tags>\n<tags>national</tags>\n<tags>sit</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>pscott</by>\n<timestamp>2017-02-17T13:58:32.585159</timestamp>\n</audit_log>\n</social_media_post>",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (user, post, likes...) and a nesting depth of 3.\n2. Identify the target format requirements: TOML requires strict syntax. Define hierarchy using dot-notation or [section] headers.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nuser = \"fcortez\"\npost = \"Before two exactly last save affect. Why major challenge strong gas far yard.\"\nlikes = 176\n[[audit_log]]\naction = \"created\"\nby = \"pscott\"\ntimestamp = \"2017-02-17T13:58:32.585159\"\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:06.579863\"\nversion = \"v1.0\"\ntags = [ \"deal\", \"heart\", \"value\", \"national\", \"sit\",]",
"role": "assistant"
}
] |
merged_dedup_00024
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML.",
"role": "system"
},
{
"content": "Reformat the YAML below into XML:\npaper_id: arXiv:2024.84903\ntitle: Stand-alone scalable encryption\nauthors:\n- name: John Shields\n affiliation: Schaefer LLC\n email: wigginsshawn@example.net\n- name: Stephanie Wilson\n affiliation: Carroll, Smith and Parker\n email: cooperjudy@example.com\n- name: Curtis Beasley\n affiliation: Ramirez and Sons\n email: bcampbell@example.com\nabstract: 'Smile relate manage realize husband government community. Prevent expert\n once authority modern.\n In individual program. Over glass they movie official. Address blue around whatever\n page scene early.'\nkeywords:\n- artist\n- responsibility\n- decade\npublication:\n venue: Nature\n year: 2022\n doi: 10.7875/QjYR",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Identify the target format requirements: XML requires strict syntax. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<research_paper>\n<paper_id>arXiv:2024.84903</paper_id>\n<title>Stand-alone scalable encryption</title>\n<authors>\n<name>John Shields</name>\n<affiliation>Schaefer LLC</affiliation>\n<email>wigginsshawn@example.net</email>\n</authors>\n<authors>\n<name>Stephanie Wilson</name>\n<affiliation>Carroll, Smith and Parker</affiliation>\n<email>cooperjudy@example.com</email>\n</authors>\n<authors>\n<name>Curtis Beasley</name>\n<affiliation>Ramirez and Sons</affiliation>\n<email>bcampbell@example.com</email>\n</authors>\n<abstract>Smile relate manage realize husband government community. Prevent expert once authority modern.\nIn individual program. Over glass they movie official. Address blue around whatever page scene early.</abstract>\n<keywords>artist</keywords>\n<keywords>responsibility</keywords>\n<keywords>decade</keywords>\n<publication>\n<venue>Nature</venue>\n<year>2022</year>\n<doi>10.7875/QjYR</doi>\n</publication>\n</research_paper>",
"role": "assistant"
}
] |
merged_dedup_00025
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ndimensions.height_cm, dimensions.depth_cm, dimensions.width_cm, flags.archived, novaLumen, nova_nova, terra_delta, nova_gamma\nTEXT:\ndimensions.height_cm: 215.8 | dimensions.depth_cm: 44.6 | dimensions.width_cm: 266.2 | flags.archived: False | novaLumen: Ember | nova_nova: Ember | terra_delta: 1000 | nova_gamma: 5354.24",
"role": "user"
},
{
"content": "novaLumen = \"Ember\"\nnova_gamma = 5354.24\nnova_nova = \"Ember\"\nterra_delta = 1000\n[dimensions]\ndepth_cm = 44.6\nheight_cm = 215.8\nwidth_cm = 266.2\n[flags]\narchived = false",
"role": "assistant"
}
] |
merged_dedup_00026
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ntags[1], flags.featured, flags.archived, tags[0], novaAtlas, lumenBeta, velox_atlas, novaLumen\nTEXT:\ntags[1]: ember | flags.featured: False | flags.archived: False | tags[0]: alpha | novaAtlas: | lumenBeta: False | velox_atlas: 7824 | novaLumen: velox",
"role": "user"
},
{
"content": "lumenBeta = false\nnovaAtlas = \"\"\nnovaLumen = \"velox\"\nvelox_atlas = 7824\ntags = [\"alpha\", \"ember\"]\n[flags]\narchived = false\nfeatured = false",
"role": "assistant"
}
] |
merged_dedup_00027
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Create a YAML representation of research paper.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The research_paper should contain a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\npaper_id: arXiv:2020.45500\ntitle: Profit-focused clear-thinking data-warehouse\nauthors:\n- name: Kathy Anderson\n affiliation: Martinez Inc\n email: wjohnson@example.org\n- name: Edward Snyder\n affiliation: Walls, Smith and Richards\n email: robert33@example.net\n- name: Tracy Rodriguez\n affiliation: Davis PLC\n email: elizabethmorrison@example.com\n- name: Clinton Carlson\n affiliation: Webb Inc\n email: allenmeyers@example.org\nabstract: 'Ground college professional also lawyer. Need up land quite material.\n Good bad this do with according. Week south often model industry it now medical.'\nkeywords:\n- lot\n- form\n- reveal\npublication:\n venue: ICLR\n year: 2020\n doi: 10.8889/HDtI",
"role": "assistant"
}
] |
merged_dedup_00028
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Convert the following TOML to CSV:\nuser = \"lori80\"\nrating = 4\ncomment = \"Direction sign week represent thing friend art.\"\n[[audit_log]]\naction = \"created\"\nby = \"fpowell\"\ntimestamp = \"2024-12-06T01:40:04.096854\"\n[[audit_log]]\naction = \"created\"\nby = \"kimberly73\"\ntimestamp = \"1986-01-28T21:51:25.896323\"\n[meta_info]\ngenerated_at = \"2026-01-22T04:03:05.005015\"\nversion = \"v5.0\"\ntags = [ \"successful\", \"every\", \"still\", \"unit\", \"score\",]",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nuser,rating,comment,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\nlori80,4,Direction sign week represent thing friend art.,2026-01-22T04:03:05.005015,v5.0,\"[\"\"successful\"\", \"\"every\"\", \"\"still\"\", \"\"unit\"\", \"\"score\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"fpowell\"\", \"\"timestamp\"\": \"\"2024-12-06T01:40:04.096854\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"kimberly73\"\", \"\"timestamp\"\": \"\"1986-01-28T21:51:25.896323\"\"}]\"",
"role": "assistant"
}
] |
merged_dedup_00029
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Create a YAML representation of product listing.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\nproduct: tell\nprice: 71.1\nstock: 0",
"role": "assistant"
}
] |
merged_dedup_00030
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Transform this data from YAML to CSV:\nuser: rruiz\nrating: 2\ncomment: Even leader compare hospital organization civil.",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nuser,rating,comment\nrruiz,2,Even leader compare hospital organization civil.",
"role": "assistant"
}
] |
merged_dedup_00031
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following toml into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nTOML:\n[[items]]\nalphaEon = false\natlasDelta = \"nova\"\ndeltaZephyr = \"Aurora\"\ngamma_terra = \"Nova\"\nomega_ember = \"atlas\"\ntags = [\"nova\", \"delta\", \"atlas\"]\n[items.dimensions]\ndepth_cm = 19.1\nheight_cm = 135.5\nwidth_cm = 102.1\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Ember\"\n[[items.meta]]\nkey = \"year\"\nvalue = 2024\n[[items]]\nauroraAlpha = 362\nauroraAtlas = 3583.79\nlumen_aurora = \"Zephyr\"\nnova_beta = 3910.61\nzephyr_aurora = true\ntags = [\"nova\", \"velox\"]\n[items.dimensions]\ndepth_cm = 86.8\nheight_cm = 299.6\nwidth_cm = 268.1\n[items.flags]\narchived = false\nfeatured = true\n[[items.components]]\nname = \"Nova\"\nqty = 3\n[[items.components]]\nname = \"Terra\"\nqty = 3\n[[items]]\natlas_lumen = true\nnotes = \"Aurora\"\nnovaAurora = 7025.9\nvelox_zephyr = \"gamma\"\nzephyrDelta = \"Delta\"\nzephyr_lumen = \"aurora\"\ntags = [\"ember\", \"nova\", \"ember\"]\n[items.dimensions]\ndepth_cm = 13.7\nheight_cm = 75.4\nwidth_cm = 52.0\n[items.flags]\narchived = true\nfeatured = true\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Atlas\"\n[[items.meta]]\nkey = \"year\"\nvalue = 1965\n[[items]]\nbetaTerra = 4481\nbeta_eon = 6461.1\ndeltaEon = 6036.2\ndelta_alpha = 7950\nlumen_beta = 1672\nnovaLumen = 9982.18\nomegaEon = 2072\nterra_aurora = \"delta\"\ntags = [\"omega\", \"velox\", \"gamma\"]\n[items.dimensions]\ndepth_cm = 39.9\nheight_cm = 109.4\nwidth_cm = 158.4\n[items.flags]\narchived = false\nfeatured = true\n[[items.components]]\nname = \"Nova\"\nqty = 3\n[[items.components]]\nname = \"Gamma\"\nqty = 3\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Alpha\"\n[[items.meta]]\nkey = \"year\"\nvalue = 1985",
"role": "user"
},
{
"content": "items:\n- atlasDelta: nova\n alphaEon: false\n gamma_terra: Nova\n omega_ember: atlas\n deltaZephyr: Aurora\n dimensions:\n height_cm: 135.5\n width_cm: 102.1\n depth_cm: 19.1\n tags:\n - nova\n - delta\n - atlas\n meta:\n - key: origin\n value: Ember\n - key: year\n value: 2024\n- zephyr_aurora: true\n auroraAtlas: 3583.79\n nova_beta: 3910.61\n auroraAlpha: 362\n lumen_aurora: Zephyr\n dimensions:\n height_cm: 299.6\n width_cm: 268.1\n depth_cm: 86.8\n flags:\n featured: true\n archived: false\n tags:\n - nova\n - velox\n components:\n - name: Nova\n qty: 3\n - name: Terra\n qty: 3\n- atlas_lumen: true\n zephyr_lumen: aurora\n zephyrDelta: Delta\n novaAurora: 7025.9\n velox_zephyr: gamma\n dimensions:\n height_cm: 75.4\n width_cm: 52.0\n depth_cm: 13.7\n flags:\n featured: true\n archived: true\n tags:\n - ember\n - nova\n - ember\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 1965\n notes: Aurora\n- terra_aurora: delta\n novaLumen: 9982.18\n omegaEon: 2072\n delta_alpha: 7950\n beta_eon: 6461.1\n deltaEon: 6036.2\n lumen_beta: 1672\n betaTerra: 4481\n dimensions:\n height_cm: 109.4\n width_cm: 158.4\n depth_cm: 39.9\n flags:\n featured: true\n archived: false\n tags:\n - omega\n - velox\n - gamma\n meta:\n - key: origin\n value: Alpha\n - key: year\n value: 1985\n components:\n - name: Nova\n qty: 3\n - name: Gamma\n qty: 3",
"role": "assistant"
}
] |
merged_dedup_00032
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following csv into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nCSV:\nalphaBeta,alphaTerra,alpha_eon,atlas_delta,atlas_omega,auroraAlpha,aurora_gamma,aurora_nova,beta_alpha,beta_zephyr,components,deltaBeta,delta_velox,dimensions,emberLumen,eonVelox,flags,gamma_omega,lumen_delta,meta,notes,novaDelta,nova_aurora,omega_omega,tags,veloxBeta,veloxDelta,veloxOmega,zephyrGamma,zephyr_delta,zephyr_lumen\n,,8686,,,,8856,9587,6607.17,,\"[{\"\"name\"\": \"\"Nova\"\", \"\"qty\"\": 2}, {\"\"name\"\": \"\"Lumen\"\", \"\"qty\"\": 1}]\",,,,,true,\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Alpha\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1970}]\",,,true,,\"[\"\"omega\"\", \"\"velox\"\"]\",5515,,,5368.87,,\n457,,,,,,,,,,\"[{\"\"name\"\": \"\"Alpha\"\", \"\"qty\"\": 3}, {\"\"name\"\": \"\"Nova\"\", \"\"qty\"\": 4}]\",3792,velox,\"{\"\"height_cm\"\": 229.4, \"\"width_cm\"\": 192.4, \"\"depth_cm\"\": 66.2}\",,,\"{\"\"featured\"\": true, \"\"archived\"\": true}\",2626,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Velox\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2025}]\",,6442,,,\"[\"\"aurora\"\", \"\"velox\"\"]\",Lumen,aurora,,,,\n,,,3495.59,true,3173,,,,true,,,,,Delta,,\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Beta\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2004}]\",,,,,\"[\"\"aurora\"\", \"\"delta\"\", \"\"atlas\"\", \"\"zephyr\"\"]\",,,atlas,,,\n,2054,8146,,,,,,,,\"[{\"\"name\"\": \"\"Velox\"\", \"\"qty\"\": 3}, {\"\"name\"\": \"\"Omega\"\", \"\"qty\"\": 3}]\",,,\"{\"\"height_cm\"\": 212.5, \"\"width_cm\"\": 44.2, \"\"depth_cm\"\": 43.8}\",,,\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,terra,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Terra\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1964}]\",Ember,,,delta,\"[\"\"delta\"\", \"\"omega\"\", \"\"eon\"\"]\",,,,,nova,8305.99",
"role": "user"
},
{
"content": "items:\n- beta_alpha: 6607.17\n veloxBeta: 5515\n aurora_nova: 9587\n zephyrGamma: 5368.87\n aurora_gamma: 8856\n eonVelox: true\n alpha_eon: 8686\n nova_aurora: true\n flags:\n featured: false\n archived: false\n tags:\n - omega\n - velox\n meta:\n - key: origin\n value: Alpha\n - key: year\n value: 1970\n components:\n - name: Nova\n qty: 2\n - name: Lumen\n qty: 1\n- gamma_omega: 2626\n veloxBeta: Lumen\n deltaBeta: 3792\n novaDelta: 6442\n delta_velox: velox\n alphaBeta: 457\n veloxDelta: aurora\n dimensions:\n height_cm: 229.4\n width_cm: 192.4\n depth_cm: 66.2\n flags:\n featured: true\n archived: true\n tags:\n - aurora\n - velox\n meta:\n - key: origin\n value: Velox\n - key: year\n value: 2025\n components:\n - name: Alpha\n qty: 3\n - name: Nova\n qty: 4\n- beta_zephyr: true\n emberLumen: Delta\n veloxOmega: atlas\n atlas_omega: true\n auroraAlpha: 3173\n atlas_delta: 3495.59\n flags:\n featured: false\n archived: false\n tags:\n - aurora\n - delta\n - atlas\n - zephyr\n meta:\n - key: origin\n value: Beta\n - key: year\n value: 2004\n- zephyr_delta: nova\n alphaTerra: 2054\n lumen_delta: terra\n omega_omega: delta\n zephyr_lumen: 8305.99\n alpha_eon: 8146\n dimensions:\n height_cm: 212.5\n width_cm: 44.2\n depth_cm: 43.8\n flags:\n featured: false\n archived: false\n tags:\n - delta\n - omega\n - eon\n meta:\n - key: origin\n value: Terra\n - key: year\n value: 1964\n components:\n - name: Velox\n qty: 3\n - name: Omega\n qty: 3\n notes: Ember",
"role": "assistant"
}
] |
merged_dedup_00033
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following json into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nJSON:\n{\"items\": [{\"betaEon\": true, \"veloxTerra\": true, \"eon_beta\": \"\", \"delta_atlas\": false, \"zephyrBeta\": false, \"emberZephyr\": 6044, \"gamma_alpha\": false, \"nova_atlas\": 7913, \"alphaNova\": \"omega\", \"dimensions\": {\"height_cm\": 99.7, \"width_cm\": 123.8, \"depth_cm\": 36.9}, \"flags\": {\"featured\": false, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Ember\"}, {\"key\": \"year\", \"value\": 1903}], \"components\": [{\"name\": \"Eon\", \"qty\": 4}, {\"name\": \"Nova\", \"qty\": 2}]}, {\"alphaOmega\": 9028, \"eonGamma\": 4713, \"zephyrGamma\": 5925.3, \"zephyr_terra\": true, \"omega_atlas\": 8322, \"beta_gamma\": 9645.41, \"auroraAlpha\": 559, \"omegaOmega\": 3920, \"flags\": {\"featured\": false, \"archived\": true}, \"meta\": [{\"key\": \"origin\", \"value\": \"Nova\"}, {\"key\": \"year\", \"value\": 1943}]}, {\"terraEon\": \"\", \"lumenTerra\": \"\", \"aurora_lumen\": 971, \"omega_ember\": 2830, \"alpha_zephyr\": \"Alpha\", \"velox_terra\": 7016, \"novaAurora\": true, \"dimensions\": {\"height_cm\": 155.2, \"width_cm\": 163.8, \"depth_cm\": 54.6}, \"flags\": {\"featured\": false, \"archived\": false}, \"notes\": \"Atlas\"}, {\"gammaAurora\": 5634.69, \"eon_aurora\": \"Nova\", \"auroraNova\": true, \"novaAurora\": 6626, \"nova_terra\": \"Zephyr\", \"alphaDelta\": 4837, \"betaNova\": true, \"dimensions\": {\"height_cm\": 209.7, \"width_cm\": 70.1, \"depth_cm\": 62.4}, \"flags\": {\"featured\": false, \"archived\": false}, \"tags\": [\"ember\", \"atlas\", \"nova\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Aurora\"}, {\"key\": \"year\", \"value\": 1993}]}, {\"terra_delta\": true, \"betaLumen\": \"Terra\", \"lumen_beta\": \"\", \"auroraVelox\": 6566.92, \"terra_gamma\": 7692.73, \"aurora_alpha\": \"Eon\", \"dimensions\": {\"height_cm\": 177.5, \"width_cm\": 34.3, \"depth_cm\": 37.5}, \"flags\": {\"featured\": false, \"archived\": true}, \"meta\": [{\"key\": \"origin\", \"value\": \"Aurora\"}, {\"key\": \"year\", \"value\": 1942}], \"notes\": \"Lumen\"}, {\"delta_ember\": \"aurora\", \"beta_terra\": 9893, \"beta_delta\": false, \"zephyr_omega\": \"Aurora\", \"veloxBeta\": \"atlas\", \"nova_delta\": \"beta\", \"dimensions\": {\"height_cm\": 90.6, \"width_cm\": 97.6, \"depth_cm\": 93.8}, \"notes\": \"Ember\"}]}",
"role": "user"
},
{
"content": "items:\n- betaEon: true\n veloxTerra: true\n eon_beta: ''\n delta_atlas: false\n zephyrBeta: false\n emberZephyr: 6044\n gamma_alpha: false\n nova_atlas: 7913\n alphaNova: omega\n dimensions:\n height_cm: 99.7\n width_cm: 123.8\n depth_cm: 36.9\n flags:\n featured: false\n archived: false\n meta:\n - key: origin\n value: Ember\n - key: year\n value: 1903\n components:\n - name: Eon\n qty: 4\n - name: Nova\n qty: 2\n- alphaOmega: 9028\n eonGamma: 4713\n zephyrGamma: 5925.3\n zephyr_terra: true\n omega_atlas: 8322\n beta_gamma: 9645.41\n auroraAlpha: 559\n omegaOmega: 3920\n flags:\n featured: false\n archived: true\n meta:\n - key: origin\n value: Nova\n - key: year\n value: 1943\n- terraEon: ''\n lumenTerra: ''\n aurora_lumen: 971\n omega_ember: 2830\n alpha_zephyr: Alpha\n velox_terra: 7016\n novaAurora: true\n dimensions:\n height_cm: 155.2\n width_cm: 163.8\n depth_cm: 54.6\n flags:\n featured: false\n archived: false\n notes: Atlas\n- gammaAurora: 5634.69\n eon_aurora: Nova\n auroraNova: true\n novaAurora: 6626\n nova_terra: Zephyr\n alphaDelta: 4837\n betaNova: true\n dimensions:\n height_cm: 209.7\n width_cm: 70.1\n depth_cm: 62.4\n flags:\n featured: false\n archived: false\n tags:\n - ember\n - atlas\n - nova\n meta:\n - key: origin\n value: Aurora\n - key: year\n value: 1993\n- terra_delta: true\n betaLumen: Terra\n lumen_beta: ''\n auroraVelox: 6566.92\n terra_gamma: 7692.73\n aurora_alpha: Eon\n dimensions:\n height_cm: 177.5\n width_cm: 34.3\n depth_cm: 37.5\n flags:\n featured: false\n archived: true\n meta:\n - key: origin\n value: Aurora\n - key: year\n value: 1942\n notes: Lumen\n- delta_ember: aurora\n beta_terra: 9893\n beta_delta: false\n zephyr_omega: Aurora\n veloxBeta: atlas\n nova_delta: beta\n dimensions:\n height_cm: 90.6\n width_cm: 97.6\n depth_cm: 93.8\n notes: Ember",
"role": "assistant"
}
] |
merged_dedup_00034
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON.",
"role": "system"
},
{
"content": "Convert the following TOML to JSON:\ntimestamp = \"2026-01-22T04:03:07.720466\"\nlevel = \"ERROR\"\nmessage = \"Sign similar onto appear.\"",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input TOML structure: It represents a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Identify the target format requirements: JSON requires strict syntax. Ensure all keys are quoted and nested structures use curly braces.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\n{\n \"timestamp\": \"2026-01-22T04:03:07.720466\",\n \"level\": \"ERROR\",\n \"message\": \"Sign similar onto appear.\"\n}",
"role": "assistant"
}
] |
merged_dedup_00035
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Reformat the YAML below into CSV:\npaper_id: arXiv:2020.66871\ntitle: Virtual heuristic circuit\nauthors:\n- name: Troy Hill\n affiliation: Lee, Long and White\n email: debra10@example.org\n- name: Donna Ryan\n affiliation: Clark, Miller and Williams\n email: tgrant@example.com\n- name: Brandon Gonzalez\n affiliation: Stewart-Mason\n email: bakeremily@example.com\nabstract: 'Buy she kid heavy staff respond assume.\n Team just first ten important themselves short discover. Everyone assume training.\n Security direction model.'\nkeywords:\n- then\n- new\n- often\n- billion\npublication:\n venue: Science\n year: 2022\n doi: 10.1028/bLjd",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input YAML structure: It represents a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\npaper_id,title,authors,abstract,keywords,publication.venue,publication.year,publication.doi\narXiv:2020.66871,Virtual heuristic circuit,\"[{\"\"name\"\": \"\"Troy Hill\"\", \"\"affiliation\"\": \"\"Lee, Long and White\"\", \"\"email\"\": \"\"debra10@example.org\"\"}, {\"\"name\"\": \"\"Donna Ryan\"\", \"\"affiliation\"\": \"\"Clark, Miller and Williams\"\", \"\"email\"\": \"\"tgrant@example.com\"\"}, {\"\"name\"\": \"\"Brandon Gonzalez\"\", \"\"affiliation\"\": \"\"Stewart-Mason\"\", \"\"email\"\": \"\"bakeremily@example.com\"\"}]\",\"Buy she kid heavy staff respond assume.\nTeam just first ten important themselves short discover. Everyone assume training. Security direction model.\",\"[\"\"then\"\", \"\"new\"\", \"\"often\"\", \"\"billion\"\"]\",Science,2022,10.1028/bLjd",
"role": "assistant"
}
] |
merged_dedup_00036
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML.",
"role": "system"
},
{
"content": "Create a TOML representation of contract.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The contract should contain a dictionary with 3 root fields (contract, parties, signed) and a nesting depth of 2.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\ncontract = \"deploy integrated ROI\"\nparties = [ \"Nelson-Hamilton\", \"Jackson-Burton\",]\nsigned = true",
"role": "assistant"
}
] |
merged_dedup_00037
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following csv into XML.\nReturn ONLY XML.\nCSV:\natlasAurora,atlasNova,aurora_alpha,aurora_lumen,betaDelta,betaVelox,components,delta_beta,delta_zephyr,dimensions,ember_velox,eonGamma,flags,gamma_aurora,gamma_lumen,meta,notes,nova_nova,omegaGamma,omega_atlas,omega_omega,tags,terra_lumen,veloxGamma,zephyr_eon\n,,,,,,\"[{\"\"name\"\": \"\"Atlas\"\", \"\"qty\"\": 2}, {\"\"name\"\": \"\"Terra\"\", \"\"qty\"\": 4}]\",,6173.6,\"{\"\"height_cm\"\": 212.2, \"\"width_cm\"\": 196.0, \"\"depth_cm\"\": 91.7}\",Aurora,,\"{\"\"featured\"\": true, \"\"archived\"\": false}\",gamma,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Lumen\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2016}]\",Beta,,Delta,616.23,,\"[\"\"eon\"\", \"\"atlas\"\", \"\"nova\"\", \"\"alpha\"\"]\",false,,\n4757,,8587.08,Lumen,6749,,\"[{\"\"name\"\": \"\"Lumen\"\", \"\"qty\"\": 2}, {\"\"name\"\": \"\"Nova\"\", \"\"qty\"\": 2}]\",,,\"{\"\"height_cm\"\": 70.3, \"\"width_cm\"\": 232.7, \"\"depth_cm\"\": 75.8}\",,atlas,\"{\"\"featured\"\": true, \"\"archived\"\": false}\",,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Omega\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2019}]\",Lumen,true,,,,\"[\"\"ember\"\", \"\"eon\"\"]\",,Lumen,377.73\n,terra,,,,eon,,omega,,\"{\"\"height_cm\"\": 73.8, \"\"width_cm\"\": 28.5, \"\"depth_cm\"\": 26.8}\",,,\"{\"\"featured\"\": true, \"\"archived\"\": true}\",,5507,,,,,,3507.81,\"[\"\"nova\"\", \"\"eon\"\", \"\"alpha\"\"]\",,,",
"role": "user"
},
{
"content": "<items><items><omegaGamma>Delta</omegaGamma><gamma_aurora>gamma</gamma_aurora><delta_zephyr>6173.6</delta_zephyr><ember_velox>Aurora</ember_velox><omega_atlas>616.23</omega_atlas><terra_lumen>false</terra_lumen><dimensions><height_cm>212.2</height_cm><width_cm>196.0</width_cm><depth_cm>91.7</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>eon</tags><tags>atlas</tags><tags>nova</tags><tags>alpha</tags><meta><key>origin</key><value>Lumen</value></meta><meta><key>year</key><value>2016</value></meta><components><name>Atlas</name><qty>2</qty></components><components><name>Terra</name><qty>4</qty></components><notes>Beta</notes></items><items><eonGamma>atlas</eonGamma><atlasAurora>4757</atlasAurora><zephyr_eon>377.73</zephyr_eon><betaDelta>6749</betaDelta><aurora_lumen>Lumen</aurora_lumen><veloxGamma>Lumen</veloxGamma><aurora_alpha>8587.08</aurora_alpha><nova_nova>true</nova_nova><dimensions><height_cm>70.3</height_cm><width_cm>232.7</width_cm><depth_cm>75.8</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>ember</tags><tags>eon</tags><meta><key>origin</key><value>Omega</value></meta><meta><key>year</key><value>2019</value></meta><components><name>Lumen</name><qty>2</qty></components><components><name>Nova</name><qty>2</qty></components><notes>Lumen</notes></items><items><omega_omega>3507.81</omega_omega><delta_beta>omega</delta_beta><atlasNova>terra</atlasNova><gamma_lumen>5507</gamma_lumen><betaVelox>eon</betaVelox><dimensions><height_cm>73.8</height_cm><width_cm>28.5</width_cm><depth_cm>26.8</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>nova</tags><tags>eon</tags><tags>alpha</tags></items></items>",
"role": "assistant"
}
] |
merged_dedup_00038
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\ndimensions.depth_cm, tags[0], flags.archived, tags[1], emberBeta, aurora_lumen, omega_gamma, zephyr_omega\nTEXT:\ndimensions.depth_cm: 15.7 | tags[0]: nova | flags.archived: True | tags[1]: atlas | emberBeta: nova | aurora_lumen: 8931 | omega_gamma: 7951.7 | zephyr_omega: True",
"role": "user"
},
{
"content": "dimensions:\n depth_cm: 15.7\ntags:\n- nova\n- atlas\nflags:\n archived: true\nemberBeta: nova\naurora_lumen: 8931\nomega_gamma: 7951.7\nzephyr_omega: true",
"role": "assistant"
}
] |
merged_dedup_00039
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ndimensions.height_cm, dimensions.depth_cm, tags[0], tags[1], eonOmega, terraEon, atlas_beta, eon_alpha\nTEXT:\ndimensions.height_cm: 206.4 | dimensions.depth_cm: 26.8 | tags[0]: gamma | tags[1]: beta | eonOmega: alpha | terraEon: 7321 | atlas_beta: 9676 | eon_alpha: eon",
"role": "user"
},
{
"content": "atlas_beta = 9676\neonOmega = \"alpha\"\neon_alpha = \"eon\"\nterraEon = 7321\ntags = [\"gamma\", \"beta\"]\n[dimensions]\ndepth_cm = 26.8\nheight_cm = 206.4",
"role": "assistant"
}
] |
merged_dedup_00040
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Convert the following XML into YAML.\nConstraints:\n- Preserve original tag names exactly (no renaming to snake_case).\n- Child elements become mapping keys; repeated elements become lists.\n- Keep ordering and nesting as in XML.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nXML:\n<root><items><delta_gamma>Gamma</delta_gamma><velox_alpha>7938</velox_alpha><omegaBeta /><emberVelox>9485</emberVelox><veloxDelta>terra</veloxDelta><dimensions><height_cm>151.2</height_cm><width_cm>57.0</width_cm><depth_cm>17.0</depth_cm></dimensions><tags>atlas</tags><tags>aurora</tags><meta><key>origin</key><value>Zephyr</value></meta><meta><key>year</key><value>1929</value></meta><components><name>Terra</name><qty>2</qty></components><components><name>Omega</name><qty>5</qty></components></items><items><eon_lumen>7153.44</eon_lumen><eon_nova>false</eon_nova><veloxTerra>true</veloxTerra><velox_aurora>8646.71</velox_aurora><alphaAurora>zephyr</alphaAurora><lumen_delta>Delta</lumen_delta><lumenEon>6034.58</lumenEon><omega_atlas>velox</omega_atlas><dimensions><height_cm>295.2</height_cm><width_cm>269.3</width_cm><depth_cm>27.7</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>omega</tags><tags>omega</tags><tags>aurora</tags><tags>lumen</tags><meta><key>origin</key><value>Omega</value></meta><meta><key>year</key><value>1937</value></meta><notes>Atlas</notes></items><items><delta_eon>4249</delta_eon><beta_velox>omega</beta_velox><velox_atlas>2944.76</velox_atlas><atlas_atlas>terra</atlas_atlas><deltaTerra>true</deltaTerra><aurora_velox>6060</aurora_velox><dimensions><height_cm>126.8</height_cm><width_cm>245.3</width_cm><depth_cm>1.8</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><meta><key>origin</key><value>Nova</value></meta><meta><key>year</key><value>1977</value></meta></items><items><atlasAlpha>true</atlasAlpha><terraOmega>8235.04</terraOmega><velox_nova>4058.86</velox_nova><novaAurora>23.51</novaAurora><eon_lumen>true</eon_lumen><auroraNova>false</auroraNova><emberEmber>zephyr</emberEmber><flags><featured>true</featured><archived>false</archived></flags><tags>alpha</tags><tags>lumen</tags><tags>velox</tags><components><name>Terra</name><qty>1</qty></components><components><name>Velox</name><qty>1</qty></components></items><items><eonAlpha>gamma</eonAlpha><lumenNova>Alpha</lumenNova><velox_beta>delta</velox_beta><omegaAtlas>8356.95</omegaAtlas><eonDelta>9390.08</eonDelta><zephyr_velox>6206</zephyr_velox><gamma_beta /><dimensions><height_cm>147.1</height_cm><width_cm>85.1</width_cm><depth_cm>85.3</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><meta><key>origin</key><value>Atlas</value></meta><meta><key>year</key><value>2006</value></meta></items></root>",
"role": "user"
},
{
"content": "items:\n- delta_gamma: Gamma\n velox_alpha: 7938\n omegaBeta: ''\n emberVelox: 9485\n veloxDelta: terra\n dimensions:\n height_cm: 151.2\n width_cm: 57.0\n depth_cm: 17.0\n tags:\n - atlas\n - aurora\n meta:\n - key: origin\n value: Zephyr\n - key: year\n value: 1929\n components:\n - name: Terra\n qty: 2\n - name: Omega\n qty: 5\n- eon_lumen: 7153.44\n eon_nova: false\n veloxTerra: true\n velox_aurora: 8646.71\n alphaAurora: zephyr\n lumen_delta: Delta\n lumenEon: 6034.58\n omega_atlas: velox\n dimensions:\n height_cm: 295.2\n width_cm: 269.3\n depth_cm: 27.7\n flags:\n featured: false\n archived: true\n tags:\n - omega\n - omega\n - aurora\n - lumen\n meta:\n - key: origin\n value: Omega\n - key: year\n value: 1937\n notes: Atlas\n- delta_eon: 4249\n beta_velox: omega\n velox_atlas: 2944.76\n atlas_atlas: terra\n deltaTerra: true\n aurora_velox: 6060\n dimensions:\n height_cm: 126.8\n width_cm: 245.3\n depth_cm: 1.8\n flags:\n featured: false\n archived: false\n meta:\n - key: origin\n value: Nova\n - key: year\n value: 1977\n- atlasAlpha: true\n terraOmega: 8235.04\n velox_nova: 4058.86\n novaAurora: 23.51\n eon_lumen: true\n auroraNova: false\n emberEmber: zephyr\n flags:\n featured: true\n archived: false\n tags:\n - alpha\n - lumen\n - velox\n components:\n - name: Terra\n qty: 1\n - name: Velox\n qty: 1\n- eonAlpha: gamma\n lumenNova: Alpha\n velox_beta: delta\n omegaAtlas: 8356.95\n eonDelta: 9390.08\n zephyr_velox: 6206\n gamma_beta: ''\n dimensions:\n height_cm: 147.1\n width_cm: 85.1\n depth_cm: 85.3\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 2006",
"role": "assistant"
}
] |
merged_dedup_00041
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.featured, tags[1], dimensions.depth_cm, dimensions.height_cm, zephyr_zephyr, eonAtlas, auroraAurora, omegaEmber\nTEXT:\nflags.featured: True | tags[1]: zephyr | dimensions.depth_cm: 70.2 | dimensions.height_cm: 121.1 | zephyr_zephyr: lumen | eonAtlas: alpha | auroraAurora: Beta | omegaEmber: Alpha",
"role": "user"
},
{
"content": "auroraAurora = \"Beta\"\neonAtlas = \"alpha\"\nomegaEmber = \"Alpha\"\nzephyr_zephyr = \"lumen\"\ntags = [\"\", \"zephyr\"]\n[dimensions]\ndepth_cm = 70.2\nheight_cm = 121.1\n[flags]\nfeatured = true",
"role": "assistant"
}
] |
merged_dedup_00042
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following csv into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nCSV:\nalpha_atlas,alpha_nova,atlas_delta,atlas_nova,atlas_velox,auroraBeta,auroraLumen,auroraOmega,aurora_atlas,betaAlpha,betaBeta,betaEon,betaOmega,beta_zephyr,components,deltaAurora,deltaDelta,delta_nova,delta_velox,dimensions,emberZephyr,ember_beta,ember_ember,eonOmega,flags,gammaAlpha,gammaGamma,gamma_delta,gamma_lumen,lumen_ember,meta,notes,novaBeta,novaDelta,novaLumen,nova_alpha,nova_atlas,nova_gamma,nova_terra,nova_zephyr,omegaBeta,omegaNova,tags,terraGamma,veloxBeta,veloxDelta,veloxEon,veloxNova,veloxOmega,velox_atlas,velox_lumen,zephyrEon\n,5168.99,,,,,,,,,,,,,,,,,,\"{\"\"height_cm\"\": 173.5, \"\"width_cm\"\": 105.7, \"\"depth_cm\"\": 18.6}\",,,,,\"{\"\"featured\"\": false, \"\"archived\"\": true}\",,,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Gamma\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1944}]\",,,,,6001,,,,,lumen,,\"[\"\"beta\"\", \"\"lumen\"\", \"\"omega\"\"]\",,,,,,,,false,\n,,beta,,Aurora,,,,,Velox,,,,8899.32,,,,,,\"{\"\"height_cm\"\": 178.8, \"\"width_cm\"\": 171.7, \"\"depth_cm\"\": 17.5}\",,Beta,,,\"{\"\"featured\"\": true, \"\"archived\"\": false}\",,,Alpha,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Nova\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2009}]\",,,,,,,,,,,,\"[\"\"ember\"\", \"\"alpha\"\"]\",,,4287,,1.2,,,,\n,,,,,,,,true,,,,,,,,,,,\"{\"\"height_cm\"\": 253.8, \"\"width_cm\"\": 153.7, \"\"depth_cm\"\": 60.9}\",,,,,\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,alpha,,Gamma,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Atlas\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1925}]\",Eon,,,262.19,,,false,,,,,\"[\"\"ember\"\", \"\"lumen\"\", \"\"delta\"\"]\",,,,,,,6362.11,,9243\n,,,Nova,,,,,,,,velox,,,\"[{\"\"name\"\": \"\"Atlas\"\", \"\"qty\"\": 1}, {\"\"name\"\": \"\"Nova\"\", \"\"qty\"\": 1}]\",,,,,\"{\"\"height_cm\"\": 21.0, \"\"width_cm\"\": 49.3, \"\"depth_cm\"\": 67.5}\",,,,,\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,,,,,,,,delta,,,4582.02,,true,8374.9,,,,,1433,,terra,,,,,\n,,,,,false,,,,,3012,,terra,,,,,,,\"{\"\"height_cm\"\": 21.8, \"\"width_cm\"\": 253.9, \"\"depth_cm\"\": 43.6}\",5815.39,,,5806,,,7503,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Atlas\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1957}]\",,omega,,,,,,,,,Velox,\"[\"\"terra\"\", \"\"lumen\"\", \"\"gamma\"\"]\",,,,,,,,,\nEmber,,,,,,delta,true,,,,,,,\"[{\"\"name\"\": \"\"Aurora\"\", \"\"qty\"\": 4}, {\"\"name\"\": \"\"Beta\"\", \"\"qty\"\": 1}]\",Nova,true,Beta,,,,,4301,,\"{\"\"featured\"\": false, \"\"archived\"\": true}\",,,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Terra\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1943}]\",,,,,,,,,,,,\"[\"\"terra\"\", \"\"terra\"\", \"\"gamma\"\"]\",,,,,,Alpha,,,",
"role": "user"
},
{
"content": "items:\n- nova_alpha: 6001\n omegaBeta: lumen\n velox_lumen: false\n alpha_nova: 5168.99\n gammaAlpha: ''\n dimensions:\n height_cm: 173.5\n width_cm: 105.7\n depth_cm: 18.6\n flags:\n featured: false\n archived: true\n tags:\n - beta\n - lumen\n - omega\n meta:\n - key: origin\n value: Gamma\n - key: year\n value: 1944\n notes: ''\n- veloxDelta: 4287\n veloxNova: 1.2\n atlas_velox: Aurora\n ember_beta: Beta\n atlas_delta: beta\n betaAlpha: Velox\n gamma_delta: Alpha\n beta_zephyr: 8899.32\n dimensions:\n height_cm: 178.8\n width_cm: 171.7\n depth_cm: 17.5\n flags:\n featured: true\n archived: false\n tags:\n - ember\n - alpha\n meta:\n - key: origin\n value: Nova\n - key: year\n value: 2009\n- velox_atlas: 6362.11\n zephyrEon: 9243\n lumen_ember: ''\n gammaGamma: alpha\n novaLumen: 262.19\n gamma_lumen: Gamma\n nova_gamma: false\n aurora_atlas: true\n dimensions:\n height_cm: 253.8\n width_cm: 153.7\n depth_cm: 60.9\n flags:\n featured: false\n archived: false\n tags:\n - ember\n - lumen\n - delta\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 1925\n notes: Eon\n- nova_zephyr: 8374.9\n betaEon: velox\n atlas_nova: Nova\n nova_atlas: 4582.02\n veloxEon: terra\n novaDelta: delta\n veloxBeta: 1433\n nova_terra: true\n dimensions:\n height_cm: 21.0\n width_cm: 49.3\n depth_cm: 67.5\n flags:\n featured: false\n archived: false\n components:\n - name: Atlas\n qty: 1\n - name: Nova\n qty: 1\n- terraGamma: ''\n novaBeta: omega\n betaBeta: 3012\n eonOmega: 5806\n emberZephyr: 5815.39\n betaOmega: terra\n omegaNova: Velox\n auroraBeta: false\n gammaGamma: 7503\n dimensions:\n height_cm: 21.8\n width_cm: 253.9\n depth_cm: 43.6\n tags:\n - terra\n - lumen\n - gamma\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 1957\n- veloxOmega: Alpha\n deltaAurora: Nova\n deltaDelta: true\n alpha_atlas: Ember\n delta_nova: Beta\n auroraLumen: delta\n auroraOmega: true\n ember_ember: 4301\n delta_velox: ''\n flags:\n featured: false\n archived: true\n tags:\n - terra\n - terra\n - gamma\n meta:\n - key: origin\n value: Terra\n - key: year\n value: 1943\n components:\n - name: Aurora\n qty: 4\n - name: Beta\n qty: 1",
"role": "assistant"
}
] |
merged_dedup_00043
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON.",
"role": "system"
},
{
"content": "Create a JSON representation of news article.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 5 root fields (headline, body, author...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\n{\n \"headline\": \"Laugh detail feeling film.\",\n \"body\": \"Blood ability subject include. Green citizen seem happy. Major four shake major expert forget clearly.\",\n \"author\": \"Jonathan Reynolds\",\n \"meta_info\": {\n \"generated_at\": \"2026-01-22T04:03:04.957843\",\n \"version\": \"v5.0\",\n \"tags\": [\n \"account\",\n \"leg\",\n \"yard\",\n \"agency\",\n \"clear\"\n ]\n },\n \"audit_log\": [\n {\n \"action\": \"created\",\n \"by\": \"linda04\",\n \"timestamp\": \"1999-09-21T16:45:10.864815\"\n }\n ]\n}",
"role": "assistant"
}
] |
merged_dedup_00044
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Create a YAML representation of product listing.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The product_listing should contain a dictionary with 3 root fields (product, price, stock) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\nproduct: live\nprice: 22.45\nstock: 49",
"role": "assistant"
}
] |
merged_dedup_00045
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ntags[0], dimensions.height_cm, tags[1], dimensions.depth_cm, alphaDelta, beta_terra, ember_nova, terra_omega\nTEXT:\ntags[0]: gamma | dimensions.height_cm: 69.1 | tags[1]: eon | dimensions.depth_cm: 100.0 | alphaDelta: True | beta_terra: False | ember_nova: Omega | terra_omega: 1638.06",
"role": "user"
},
{
"content": "alphaDelta = true\nbeta_terra = false\nember_nova = \"Omega\"\nterra_omega = 1638.06\ntags = [\"gamma\", \"eon\"]\n[dimensions]\ndepth_cm = 100.0\nheight_cm = 69.1",
"role": "assistant"
}
] |
merged_dedup_00046
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.archived, flags.featured, zephyr_alpha, velox_ember, deltaZephyr, notes, alpha_delta, novaGamma\nTEXT:\nflags.archived: False | flags.featured: True | zephyr_alpha: 8398 | velox_ember: Aurora | deltaZephyr: True | notes: Nova | alpha_delta: ember | novaGamma: Atlas",
"role": "user"
},
{
"content": "alpha_delta = \"ember\"\ndeltaZephyr = true\nnotes = \"Nova\"\nnovaGamma = \"Atlas\"\nvelox_ember = \"Aurora\"\nzephyr_alpha = 8398\n[flags]\narchived = false\nfeatured = true",
"role": "assistant"
}
] |
merged_dedup_00047
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML.",
"role": "system"
},
{
"content": "Create a XML representation of customer review.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The customer_review should contain a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>dmendez</user>\n<rating>2</rating>\n<comment>Up show best country trade.</comment>\n</customer_review>",
"role": "assistant"
}
] |
merged_dedup_00048
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.archived, tags[1], dimensions.depth_cm, flags.featured, delta_nova, terraAlpha, terraAurora, lumen_delta\nTEXT:\nflags.archived: True | tags[1]: beta | dimensions.depth_cm: 29.3 | flags.featured: False | delta_nova: lumen | terraAlpha: aurora | terraAurora: 4103 | lumen_delta: 2790.11",
"role": "user"
},
{
"content": "delta_nova = \"lumen\"\nlumen_delta = 2790.11\nterraAlpha = \"aurora\"\nterraAurora = 4103\ntags = [\"\", \"beta\"]\n[dimensions]\ndepth_cm = 29.3\n[flags]\narchived = true\nfeatured = false",
"role": "assistant"
}
] |
merged_dedup_00049
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\nflags.archived, flags.featured, tags[1], tags[0], deltaAtlas, nova_lumen, omegaOmega, terraVelox\nTEXT:\nflags.archived: False | flags.featured: True | tags[1]: alpha | tags[0]: omega | deltaAtlas: Alpha | nova_lumen: 504.28 | omegaOmega: ember | terraVelox:",
"role": "user"
},
{
"content": "flags:\n archived: false\n featured: true\ntags:\n- omega\n- alpha\ndeltaAtlas: Alpha\nnova_lumen: 504.28\nomegaOmega: ember\nterraVelox: ''",
"role": "assistant"
}
] |
merged_dedup_00050
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON.",
"role": "system"
},
{
"content": "Create a JSON representation of student assessment.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The student_assessment should contain a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\n{\n \"student\": \"Ariana Butler\",\n \"score\": 54,\n \"grade\": \"B\"\n}",
"role": "assistant"
}
] |
merged_dedup_00051
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following json into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nJSON:\n{\"items\": [{\"nova_ember\": 8807, \"novaZephyr\": \"beta\", \"zephyr_zephyr\": false, \"alphaDelta\": \"Gamma\", \"eon_eon\": 8012, \"veloxEon\": 4106.52, \"dimensions\": {\"height_cm\": 217.7, \"width_cm\": 153.2, \"depth_cm\": 26.9}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"delta\", \"aurora\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Velox\"}, {\"key\": \"year\", \"value\": 1900}]}, {\"betaNova\": \"\", \"terraDelta\": 3372, \"gamma_atlas\": \"eon\", \"atlas_beta\": 9094, \"atlas_alpha\": true, \"alphaNova\": false, \"zephyr_aurora\": 4194, \"emberBeta\": \"\", \"flags\": {\"featured\": true, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Ember\"}, {\"key\": \"year\", \"value\": 1949}], \"components\": [{\"name\": \"Omega\", \"qty\": 5}, {\"name\": \"Delta\", \"qty\": 2}]}, {\"nova_zephyr\": \"alpha\", \"lumenLumen\": \"Eon\", \"novaTerra\": 1485, \"nova_aurora\": 8311.03, \"deltaOmega\": 8524, \"omegaAlpha\": 9114.78, \"dimensions\": {\"height_cm\": 180.1, \"width_cm\": 90.6, \"depth_cm\": 78.3}, \"flags\": {\"featured\": false, \"archived\": true}, \"meta\": [{\"key\": \"origin\", \"value\": \"Atlas\"}, {\"key\": \"year\", \"value\": 1910}]}]}",
"role": "user"
},
{
"content": "items:\n- nova_ember: 8807\n novaZephyr: beta\n zephyr_zephyr: false\n alphaDelta: Gamma\n eon_eon: 8012\n veloxEon: 4106.52\n dimensions:\n height_cm: 217.7\n width_cm: 153.2\n depth_cm: 26.9\n flags:\n featured: true\n archived: true\n tags:\n - delta\n - aurora\n meta:\n - key: origin\n value: Velox\n - key: year\n value: 1900\n- betaNova: ''\n terraDelta: 3372\n gamma_atlas: eon\n atlas_beta: 9094\n atlas_alpha: true\n alphaNova: false\n zephyr_aurora: 4194\n emberBeta: ''\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Ember\n - key: year\n value: 1949\n components:\n - name: Omega\n qty: 5\n - name: Delta\n qty: 2\n- nova_zephyr: alpha\n lumenLumen: Eon\n novaTerra: 1485\n nova_aurora: 8311.03\n deltaOmega: 8524\n omegaAlpha: 9114.78\n dimensions:\n height_cm: 180.1\n width_cm: 90.6\n depth_cm: 78.3\n flags:\n featured: false\n archived: true\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 1910",
"role": "assistant"
}
] |
merged_dedup_00052
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following csv into XML.\nReturn ONLY XML.\nCSV:\nalphaGamma,alphaOmega,alpha_beta,alpha_terra,atlasOmega,atlasTerra,atlas_nova,atlas_velox,auroraVelox,aurora_nova,aurora_omega,aurora_velox,beta_delta,beta_omega,components,delta_beta,dimensions,flags,gammaAtlas,gammaDelta,gammaEmber,gammaLumen,gammaNova,gamma_velox,lumenDelta,lumenNova,lumenVelox,lumen_zephyr,meta,novaEmber,nova_beta,nova_ember,nova_zephyr,omega_delta,tags,terraEmber,terra_eon,velox_zephyr\n,,,,,8441.55,8847.12,,,296.02,,,,,\"[{\"\"name\"\": \"\"Delta\"\", \"\"qty\"\": 5}, {\"\"name\"\": \"\"Delta\"\", \"\"qty\"\": 4}]\",,\"{\"\"height_cm\"\": 192.0, \"\"width_cm\"\": 284.8, \"\"depth_cm\"\": 52.4}\",\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,,7260,,,,,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Eon\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1964}]\",Velox,6606.82,,,,\"[\"\"nova\"\", \"\"velox\"\"]\",,,3958\n,,,,,,,,,,,,,,\"[{\"\"name\"\": \"\"Beta\"\", \"\"qty\"\": 4}, {\"\"name\"\": \"\"Delta\"\", \"\"qty\"\": 1}]\",,\"{\"\"height_cm\"\": 24.4, \"\"width_cm\"\": 114.6, \"\"depth_cm\"\": 62.2}\",\"{\"\"featured\"\": true, \"\"archived\"\": true}\",,9862,,,,,,true,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Gamma\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1918}]\",,,9962.93,true,,\"[\"\"beta\"\", \"\"velox\"\", \"\"lumen\"\", \"\"gamma\"\"]\",true,,\n,1640,false,Terra,1280,,,,,,9878.26,,,,\"[{\"\"name\"\": \"\"Omega\"\", \"\"qty\"\": 2}, {\"\"name\"\": \"\"Alpha\"\", \"\"qty\"\": 1}]\",8585.87,\"{\"\"height_cm\"\": 238.0, \"\"width_cm\"\": 25.6, \"\"depth_cm\"\": 77.3}\",\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,,,,8874.47,,7882.35,,,,,,,,,,\"[\"\"lumen\"\", \"\"nova\"\", \"\"beta\"\", \"\"eon\"\"]\",,,\n,5623,,,,,,3347,,,,2897.43,,,,,\"{\"\"height_cm\"\": 163.5, \"\"width_cm\"\": 50.1, \"\"depth_cm\"\": 75.8}\",\"{\"\"featured\"\": false, \"\"archived\"\": true}\",1890,,,,,,,,,false,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Gamma\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1908}]\",,,,,8481,\"[\"\"gamma\"\", \"\"velox\"\"]\",,,\nAtlas,,,,,,,,,,,true,259.03,,\"[{\"\"name\"\": \"\"Zephyr\"\", \"\"qty\"\": 1}, {\"\"name\"\": \"\"Aurora\"\", \"\"qty\"\": 2}]\",,\"{\"\"height_cm\"\": 183.6, \"\"width_cm\"\": 185.5, \"\"depth_cm\"\": 17.1}\",,,,,6544.01,,velox,,,lumen,9297.43,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Zephyr\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1979}]\",,,,,,\"[\"\"eon\"\", \"\"atlas\"\"]\",,Ember,",
"role": "user"
},
{
"content": "<items><items><novaEmber>Velox</novaEmber><gammaEmber>7260</gammaEmber><nova_beta>6606.82</nova_beta><atlas_nova>8847.12</atlas_nova><aurora_nova>296.02</aurora_nova><velox_zephyr>3958</velox_zephyr><atlasTerra>8441.55</atlasTerra><dimensions><height_cm>192.0</height_cm><width_cm>284.8</width_cm><depth_cm>52.4</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><tags>nova</tags><tags>velox</tags><meta><key>origin</key><value>Eon</value></meta><meta><key>year</key><value>1964</value></meta><components><name>Delta</name><qty>5</qty></components><components><name>Delta</name><qty>4</qty></components></items><items><lumenNova>true</lumenNova><gammaDelta>9862</gammaDelta><nova_zephyr>true</nova_zephyr><beta_omega /><nova_ember>9962.93</nova_ember><terraEmber>true</terraEmber><dimensions><height_cm>24.4</height_cm><width_cm>114.6</width_cm><depth_cm>62.2</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>beta</tags><tags>velox</tags><tags>lumen</tags><tags>gamma</tags><meta><key>origin</key><value>Gamma</value></meta><meta><key>year</key><value>1918</value></meta><components><name>Beta</name><qty>4</qty></components><components><name>Delta</name><qty>1</qty></components></items><items><gammaNova>8874.47</gammaNova><atlasOmega>1280</atlasOmega><lumenDelta>7882.35</lumenDelta><delta_beta>8585.87</delta_beta><alpha_beta>false</alpha_beta><aurora_omega>9878.26</aurora_omega><alphaOmega>1640</alphaOmega><alpha_terra>Terra</alpha_terra><dimensions><height_cm>238.0</height_cm><width_cm>25.6</width_cm><depth_cm>77.3</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><tags>lumen</tags><tags>nova</tags><tags>beta</tags><tags>eon</tags><components><name>Omega</name><qty>2</qty></components><components><name>Alpha</name><qty>1</qty></components></items><items><alphaOmega>5623</alphaOmega><lumen_zephyr>false</lumen_zephyr><atlas_velox>3347</atlas_velox><gammaAtlas>1890</gammaAtlas><auroraVelox /><omega_delta>8481</omega_delta><aurora_velox>2897.43</aurora_velox><dimensions><height_cm>163.5</height_cm><width_cm>50.1</width_cm><depth_cm>75.8</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>gamma</tags><tags>velox</tags><meta><key>origin</key><value>Gamma</value></meta><meta><key>year</key><value>1908</value></meta></items><items><gammaLumen>6544.01</gammaLumen><alphaGamma>Atlas</alphaGamma><aurora_velox>true</aurora_velox><lumenVelox>lumen</lumenVelox><gamma_velox>velox</gamma_velox><beta_delta>259.03</beta_delta><terra_eon>Ember</terra_eon><lumen_zephyr>9297.43</lumen_zephyr><dimensions><height_cm>183.6</height_cm><width_cm>185.5</width_cm><depth_cm>17.1</depth_cm></dimensions><tags>eon</tags><tags>atlas</tags><meta><key>origin</key><value>Zephyr</value></meta><meta><key>year</key><value>1979</value></meta><components><name>Zephyr</name><qty>1</qty></components><components><name>Aurora</name><qty>2</qty></components></items></items>",
"role": "assistant"
}
] |
merged_dedup_00053
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output JSON.\nReturn ONLY JSON.\nATTRIBUTES:\nterraEon, gamma_gamma, gammaZephyr, auroraNova, lumenDelta, dimensions\nTEXT:\nterraEon: True | gamma_gamma: | gammaZephyr: 1636 | auroraNova: 2016 | lumenDelta: Ember | dimensions: {'height_cm': 213.3, 'width_cm': 228.4, 'depth_cm': 25.1}",
"role": "user"
},
{
"content": "{\"items\": [{\"terraEon\": true, \"gamma_gamma\": \"\", \"gammaZephyr\": 1636, \"auroraNova\": 2016, \"lumenDelta\": \"Ember\", \"dimensions\": {\"height_cm\": 213.3, \"width_cm\": 228.4, \"depth_cm\": 25.1}}]}",
"role": "assistant"
}
] |
merged_dedup_00054
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following toml into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nTOML:\n[[items]]\nbetaDelta = 5193\ndeltaEmber = 5500.35\nemberLumen = \"\"\nveloxEon = 1316\nveloxLumen = 8789\ntags = [\"ember\", \"zephyr\", \"terra\"]\n[items.dimensions]\ndepth_cm = 32.4\nheight_cm = 141.8\nwidth_cm = 191.5\n[[items.components]]\nname = \"Zephyr\"\nqty = 2\n[[items.components]]\nname = \"Lumen\"\nqty = 3\n[[items]]\nalphaAlpha = 1019.91\nalphaEon = false\natlas_alpha = 8150\ngammaAtlas = \"Nova\"\nnovaAurora = \"terra\"\ntags = [\"alpha\", \"aurora\", \"omega\"]\n[items.dimensions]\ndepth_cm = 67.5\nheight_cm = 253.1\nwidth_cm = 274.8\n[items.flags]\narchived = false\nfeatured = false\n[[items]]\natlas_atlas = 8426\nbeta_gamma = 4764.1\nemberVelox = 9242\nnova_zephyr = false\nzephyrNova = \"\"\ntags = [\"omega\", \"ember\", \"delta\"]\n[items.dimensions]\ndepth_cm = 1.8\nheight_cm = 247.7\nwidth_cm = 191.8\n[[items.components]]\nname = \"Ember\"\nqty = 4\n[[items.components]]\nname = \"Omega\"\nqty = 4\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Gamma\"\n[[items.meta]]\nkey = \"year\"\nvalue = 1902\n[[items]]\nbeta_velox = 4278\nemberBeta = \"Terra\"\nlumenBeta = \"\"\nnotes = \"\"\nomegaAurora = 521.88\nvelox_omega = true\n[items.dimensions]\ndepth_cm = 22.5\nheight_cm = 165.1\nwidth_cm = 183.6\n[items.flags]\narchived = false\nfeatured = true\n[[items.meta]]\nkey = \"origin\"\nvalue = \"Omega\"\n[[items.meta]]\nkey = \"year\"\nvalue = 2012\n[[items]]\natlas_aurora = \"gamma\"\ndeltaTerra = 7560.85\nemberTerra = \"Terra\"\neonEon = \"delta\"\nnotes = \"\"\nomega_velox = \"\"\nterraDelta = \"Velox\"\nterraZephyr = \"delta\"\nzephyr_ember = 2711\ntags = [\"beta\", \"gamma\", \"aurora\"]\n[items.dimensions]\ndepth_cm = 40.8\nheight_cm = 81.3\nwidth_cm = 35.8\n[items.flags]\narchived = false\nfeatured = false",
"role": "user"
},
{
"content": "items:\n- deltaEmber: 5500.35\n veloxLumen: 8789\n emberLumen: ''\n veloxEon: 1316\n betaDelta: 5193\n dimensions:\n height_cm: 141.8\n width_cm: 191.5\n depth_cm: 32.4\n tags:\n - ember\n - zephyr\n - terra\n components:\n - name: Zephyr\n qty: 2\n - name: Lumen\n qty: 3\n- gammaAtlas: Nova\n atlas_alpha: 8150\n alphaEon: false\n alphaAlpha: 1019.91\n novaAurora: terra\n dimensions:\n height_cm: 253.1\n width_cm: 274.8\n depth_cm: 67.5\n flags:\n featured: false\n archived: false\n tags:\n - alpha\n - aurora\n - omega\n- emberVelox: 9242\n nova_zephyr: false\n beta_gamma: 4764.1\n zephyrNova: ''\n atlas_atlas: 8426\n dimensions:\n height_cm: 247.7\n width_cm: 191.8\n depth_cm: 1.8\n tags:\n - omega\n - ember\n - delta\n meta:\n - key: origin\n value: Gamma\n - key: year\n value: 1902\n components:\n - name: Ember\n qty: 4\n - name: Omega\n qty: 4\n- beta_velox: 4278\n emberBeta: Terra\n velox_omega: true\n lumenBeta: ''\n omegaAurora: 521.88\n dimensions:\n height_cm: 165.1\n width_cm: 183.6\n depth_cm: 22.5\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Omega\n - key: year\n value: 2012\n notes: ''\n- terraZephyr: delta\n omega_velox: ''\n atlas_aurora: gamma\n emberTerra: Terra\n eonEon: delta\n zephyr_ember: 2711\n deltaTerra: 7560.85\n terraDelta: Velox\n dimensions:\n height_cm: 81.3\n width_cm: 35.8\n depth_cm: 40.8\n flags:\n featured: false\n archived: false\n tags:\n - beta\n - gamma\n - aurora\n notes: ''",
"role": "assistant"
}
] |
merged_dedup_00055
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Convert the following JSON into well-formed XML.\nConstraints:\n- Use child elements only (no XML attributes).\n- Preserve key names and their letter case exactly.\n- Represent lists by repeating child elements in order.\nReturn ONLY XML.\nJSON:\n{\"items\": [{\"atlasEon\": 65, \"delta_beta\": \"gamma\", \"gamma_eon\": 8258, \"atlasTerra\": false, \"aurora_lumen\": \"\", \"dimensions\": {\"height_cm\": 107.2, \"width_cm\": 203.4, \"depth_cm\": 92.0}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"ember\", \"atlas\", \"eon\", \"delta\"]}, {\"veloxLumen\": \"Velox\", \"gamma_beta\": \"Gamma\", \"terraTerra\": 6518.38, \"lumenLumen\": true, \"beta_atlas\": 263, \"omega_atlas\": \"\", \"omegaGamma\": false, \"auroraOmega\": \"terra\", \"omegaAurora\": \"zephyr\", \"dimensions\": {\"height_cm\": 211.0, \"width_cm\": 10.3, \"depth_cm\": 43.5}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"beta\", \"velox\", \"gamma\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Nova\"}, {\"key\": \"year\", \"value\": 1977}]}, {\"atlasTerra\": \"terra\", \"terraTerra\": 9712, \"gamma_terra\": \"delta\", \"auroraTerra\": \"Gamma\", \"omegaBeta\": \"beta\", \"dimensions\": {\"height_cm\": 205.2, \"width_cm\": 258.1, \"depth_cm\": 30.4}, \"flags\": {\"featured\": false, \"archived\": false}, \"tags\": [\"eon\", \"aurora\", \"eon\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Zephyr\"}, {\"key\": \"year\", \"value\": 1967}], \"components\": [{\"name\": \"Zephyr\", \"qty\": 3}, {\"name\": \"Zephyr\", \"qty\": 4}]}, {\"alpha_eon\": 8329.52, \"velox_ember\": 9214.32, \"zephyr_atlas\": 1702.25, \"alpha_nova\": \"delta\", \"beta_velox\": \"Aurora\", \"velox_nova\": \"ember\", \"aurora_velox\": 2531, \"dimensions\": {\"height_cm\": 121.0, \"width_cm\": 223.3, \"depth_cm\": 5.9}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"alpha\", \"omega\", \"gamma\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Zephyr\"}, {\"key\": \"year\", \"value\": 1910}]}]}",
"role": "user"
},
{
"content": "<root><items><atlasEon>65</atlasEon><delta_beta>gamma</delta_beta><gamma_eon>8258</gamma_eon><atlasTerra>false</atlasTerra><aurora_lumen /><dimensions><height_cm>107.2</height_cm><width_cm>203.4</width_cm><depth_cm>92.0</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>ember</tags><tags>atlas</tags><tags>eon</tags><tags>delta</tags></items><items><veloxLumen>Velox</veloxLumen><gamma_beta>Gamma</gamma_beta><terraTerra>6518.38</terraTerra><lumenLumen>true</lumenLumen><beta_atlas>263</beta_atlas><omega_atlas /><omegaGamma>false</omegaGamma><auroraOmega>terra</auroraOmega><omegaAurora>zephyr</omegaAurora><dimensions><height_cm>211.0</height_cm><width_cm>10.3</width_cm><depth_cm>43.5</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>beta</tags><tags>velox</tags><tags>gamma</tags><meta><key>origin</key><value>Nova</value></meta><meta><key>year</key><value>1977</value></meta></items><items><atlasTerra>terra</atlasTerra><terraTerra>9712</terraTerra><gamma_terra>delta</gamma_terra><auroraTerra>Gamma</auroraTerra><omegaBeta>beta</omegaBeta><dimensions><height_cm>205.2</height_cm><width_cm>258.1</width_cm><depth_cm>30.4</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><tags>eon</tags><tags>aurora</tags><tags>eon</tags><meta><key>origin</key><value>Zephyr</value></meta><meta><key>year</key><value>1967</value></meta><components><name>Zephyr</name><qty>3</qty></components><components><name>Zephyr</name><qty>4</qty></components></items><items><alpha_eon>8329.52</alpha_eon><velox_ember>9214.32</velox_ember><zephyr_atlas>1702.25</zephyr_atlas><alpha_nova>delta</alpha_nova><beta_velox>Aurora</beta_velox><velox_nova>ember</velox_nova><aurora_velox>2531</aurora_velox><dimensions><height_cm>121.0</height_cm><width_cm>223.3</width_cm><depth_cm>5.9</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>alpha</tags><tags>omega</tags><tags>gamma</tags><meta><key>origin</key><value>Zephyr</value></meta><meta><key>year</key><value>1910</value></meta></items></root>",
"role": "assistant"
}
] |
merged_dedup_00056
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following json into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nJSON:\n{\"items\": [{\"atlasAurora\": \"Zephyr\", \"nova_zephyr\": \"Nova\", \"beta_alpha\": \"omega\", \"betaTerra\": false, \"emberAlpha\": \"nova\", \"omegaOmega\": 1465, \"lumen_lumen\": 3330.01, \"eonAurora\": 8620.69, \"omegaLumen\": 2538, \"dimensions\": {\"height_cm\": 290.3, \"width_cm\": 269.7, \"depth_cm\": 38.0}, \"flags\": {\"featured\": true, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Delta\"}, {\"key\": \"year\", \"value\": 1959}]}, {\"gamma_delta\": \"nova\", \"emberLumen\": 8158.45, \"veloxGamma\": 2415.15, \"eonEon\": \"lumen\", \"delta_aurora\": 9602, \"betaEon\": 8640.62, \"alphaLumen\": false, \"ember_terra\": 7506, \"velox_nova\": 2954.83, \"dimensions\": {\"height_cm\": 160.6, \"width_cm\": 123.9, \"depth_cm\": 69.8}, \"flags\": {\"featured\": true, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Aurora\"}, {\"key\": \"year\", \"value\": 2005}]}, {\"alphaOmega\": \"\", \"terra_ember\": false, \"ember_omega\": true, \"deltaAtlas\": \"terra\", \"emberTerra\": false, \"atlas_omega\": 9296.74, \"alphaAurora\": 3155.55, \"dimensions\": {\"height_cm\": 42.0, \"width_cm\": 102.6, \"depth_cm\": 16.0}, \"flags\": {\"featured\": true, \"archived\": false}, \"tags\": [\"omega\", \"alpha\", \"omega\", \"velox\"], \"notes\": \"\"}, {\"beta_eon\": 8417.95, \"velox_alpha\": 9391, \"lumen_nova\": 8511.09, \"auroraAtlas\": \"\", \"gammaAtlas\": 6212, \"atlas_aurora\": false, \"omega_lumen\": \"beta\", \"flags\": {\"featured\": true, \"archived\": false}, \"tags\": [\"eon\", \"nova\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Terra\"}, {\"key\": \"year\", \"value\": 1909}]}, {\"zephyrZephyr\": \"atlas\", \"terra_eon\": \"atlas\", \"veloxAtlas\": \"Gamma\", \"betaOmega\": \"nova\", \"omegaZephyr\": \"lumen\", \"delta_gamma\": 8412, \"veloxVelox\": false, \"beta_lumen\": 3487.18, \"auroraTerra\": 6284, \"dimensions\": {\"height_cm\": 57.7, \"width_cm\": 148.7, \"depth_cm\": 40.1}, \"flags\": {\"featured\": true, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Ember\"}, {\"key\": \"year\", \"value\": 1952}], \"components\": [{\"name\": \"Alpha\", \"qty\": 2}, {\"name\": \"Ember\", \"qty\": 2}], \"notes\": \"\"}]}",
"role": "user"
},
{
"content": "items:\n- atlasAurora: Zephyr\n nova_zephyr: Nova\n beta_alpha: omega\n betaTerra: false\n emberAlpha: nova\n omegaOmega: 1465\n lumen_lumen: 3330.01\n eonAurora: 8620.69\n omegaLumen: 2538\n dimensions:\n height_cm: 290.3\n width_cm: 269.7\n depth_cm: 38.0\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Delta\n - key: year\n value: 1959\n- gamma_delta: nova\n emberLumen: 8158.45\n veloxGamma: 2415.15\n eonEon: lumen\n delta_aurora: 9602\n betaEon: 8640.62\n alphaLumen: false\n ember_terra: 7506\n velox_nova: 2954.83\n dimensions:\n height_cm: 160.6\n width_cm: 123.9\n depth_cm: 69.8\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Aurora\n - key: year\n value: 2005\n- alphaOmega: ''\n terra_ember: false\n ember_omega: true\n deltaAtlas: terra\n emberTerra: false\n atlas_omega: 9296.74\n alphaAurora: 3155.55\n dimensions:\n height_cm: 42.0\n width_cm: 102.6\n depth_cm: 16.0\n flags:\n featured: true\n archived: false\n tags:\n - omega\n - alpha\n - omega\n - velox\n notes: ''\n- beta_eon: 8417.95\n velox_alpha: 9391\n lumen_nova: 8511.09\n auroraAtlas: ''\n gammaAtlas: 6212\n atlas_aurora: false\n omega_lumen: beta\n flags:\n featured: true\n archived: false\n tags:\n - eon\n - nova\n meta:\n - key: origin\n value: Terra\n - key: year\n value: 1909\n- zephyrZephyr: atlas\n terra_eon: atlas\n veloxAtlas: Gamma\n betaOmega: nova\n omegaZephyr: lumen\n delta_gamma: 8412\n veloxVelox: false\n beta_lumen: 3487.18\n auroraTerra: 6284\n dimensions:\n height_cm: 57.7\n width_cm: 148.7\n depth_cm: 40.1\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Ember\n - key: year\n value: 1952\n components:\n - name: Alpha\n qty: 2\n - name: Ember\n qty: 2\n notes: ''",
"role": "assistant"
}
] |
merged_dedup_00057
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ndimensions.width_cm, dimensions.depth_cm, dimensions.height_cm, tags[1], auroraTerra, novaZephyr, eon_gamma, terra_atlas\nTEXT:\ndimensions.width_cm: 234.6 | dimensions.depth_cm: 43.5 | dimensions.height_cm: 295.9 | tags[1]: gamma | auroraTerra: Terra | novaZephyr: 4291 | eon_gamma: Atlas | terra_atlas: Gamma",
"role": "user"
},
{
"content": "auroraTerra = \"Terra\"\neon_gamma = \"Atlas\"\nnovaZephyr = 4291\nterra_atlas = \"Gamma\"\ntags = [\"\", \"gamma\"]\n[dimensions]\ndepth_cm = 43.5\nheight_cm = 295.9\nwidth_cm = 234.6",
"role": "assistant"
}
] |
merged_dedup_00058
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\ntags[1], dimensions.depth_cm, flags.featured, tags[0], nova_velox, zephyr_omega, gamma_alpha, omegaAurora\nTEXT:\ntags[1]: gamma | dimensions.depth_cm: 33.9 | flags.featured: True | tags[0]: omega | nova_velox: 5625 | zephyr_omega: omega | gamma_alpha: 6151 | omegaAurora: Terra",
"role": "user"
},
{
"content": "tags:\n- omega\n- gamma\ndimensions:\n depth_cm: 33.9\nflags:\n featured: true\nnova_velox: 5625\nzephyr_omega: omega\ngamma_alpha: 6151\nomegaAurora: Terra",
"role": "assistant"
}
] |
merged_dedup_00059
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML.",
"role": "system"
},
{
"content": "Create a XML representation of transaction record.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The transaction_record should contain a dictionary with 5 root fields (txn, amount, status...) and a nesting depth of 3.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<transaction_record>\n<txn>efdd22f8-a8ce-4587-a6b4-7ff26e7a5eb2</txn>\n<amount>247.76</amount>\n<status>completed</status>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.835399</generated_at>\n<version>v4.0</version>\n<tags>national</tags>\n<tags>just</tags>\n<tags>TV</tags>\n<tags>keep</tags>\n<tags>trouble</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>pfox</by>\n<timestamp>1970-10-02T19:26:34.783372</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>gwalton</by>\n<timestamp>1998-09-19T02:57:53.594795</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>baldwinaustin</by>\n<timestamp>2018-08-17T07:26:25.066663</timestamp>\n</audit_log>\n</transaction_record>",
"role": "assistant"
}
] |
merged_dedup_00060
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following json into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nJSON:\n{\"items\": [{\"eon_nova\": 1973.27, \"aurora_velox\": 7139, \"ember_zephyr\": \"terra\", \"omega_ember\": true, \"zephyr_terra\": 7378.41, \"lumen_zephyr\": 2312, \"novaAurora\": 7919.47, \"veloxGamma\": \"\", \"dimensions\": {\"height_cm\": 25.6, \"width_cm\": 63.6, \"depth_cm\": 97.7}, \"tags\": [\"aurora\", \"eon\", \"lumen\", \"atlas\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Terra\"}, {\"key\": \"year\", \"value\": 2014}]}, {\"eon_aurora\": 7354, \"terraBeta\": 2965.69, \"auroraDelta\": \"ember\", \"deltaAurora\": true, \"eon_nova\": 4647, \"velox_nova\": \"Terra\", \"dimensions\": {\"height_cm\": 156.1, \"width_cm\": 110.4, \"depth_cm\": 48.3}, \"flags\": {\"featured\": true, \"archived\": false}, \"meta\": [{\"key\": \"origin\", \"value\": \"Nova\"}, {\"key\": \"year\", \"value\": 1911}], \"components\": [{\"name\": \"Atlas\", \"qty\": 4}, {\"name\": \"Aurora\", \"qty\": 2}]}, {\"omega_eon\": \"\", \"betaGamma\": 5477, \"alpha_ember\": 3276.45, \"delta_omega\": 9374.36, \"alpha_terra\": 4220, \"atlasEmber\": 4520, \"gamma_lumen\": \"gamma\", \"ember_terra\": \"Atlas\", \"dimensions\": {\"height_cm\": 263.4, \"width_cm\": 26.9, \"depth_cm\": 37.1}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"velox\", \"zephyr\", \"alpha\", \"lumen\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Ember\"}, {\"key\": \"year\", \"value\": 1950}], \"notes\": \"\"}, {\"terraBeta\": \"ember\", \"auroraBeta\": 2769.5, \"zephyrAtlas\": \"\", \"delta_ember\": \"eon\", \"atlasGamma\": \"Gamma\", \"atlasTerra\": \"lumen\", \"dimensions\": {\"height_cm\": 222.4, \"width_cm\": 203.2, \"depth_cm\": 57.7}, \"flags\": {\"featured\": true, \"archived\": false}, \"components\": [{\"name\": \"Velox\", \"qty\": 3}, {\"name\": \"Lumen\", \"qty\": 4}]}, {\"novaVelox\": 7348, \"atlas_alpha\": 4076, \"velox_atlas\": \"Atlas\", \"lumenEon\": 7588, \"beta_zephyr\": 3696.9, \"lumenNova\": \"Omega\", \"dimensions\": {\"height_cm\": 202.3, \"width_cm\": 129.6, \"depth_cm\": 32.7}, \"tags\": [\"delta\", \"terra\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Atlas\"}, {\"key\": \"year\", \"value\": 1980}], \"components\": [{\"name\": \"Ember\", \"qty\": 4}, {\"name\": \"Terra\", \"qty\": 2}]}, {\"gamma_lumen\": \"Gamma\", \"deltaVelox\": 4472, \"aurora_nova\": 2236, \"eonOmega\": 4898, \"ember_lumen\": 6134, \"gamma_terra\": 5379, \"lumen_nova\": \"Beta\", \"atlas_eon\": false, \"terraLumen\": \"omega\", \"dimensions\": {\"height_cm\": 24.5, \"width_cm\": 44.4, \"depth_cm\": 61.7}, \"flags\": {\"featured\": false, \"archived\": false}, \"tags\": [\"delta\", \"delta\", \"omega\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Atlas\"}, {\"key\": \"year\", \"value\": 1911}], \"components\": [{\"name\": \"Delta\", \"qty\": 1}, {\"name\": \"Delta\", \"qty\": 2}]}]}",
"role": "user"
},
{
"content": "items:\n- eon_nova: 1973.27\n aurora_velox: 7139\n ember_zephyr: terra\n omega_ember: true\n zephyr_terra: 7378.41\n lumen_zephyr: 2312\n novaAurora: 7919.47\n veloxGamma: ''\n dimensions:\n height_cm: 25.6\n width_cm: 63.6\n depth_cm: 97.7\n tags:\n - aurora\n - eon\n - lumen\n - atlas\n meta:\n - key: origin\n value: Terra\n - key: year\n value: 2014\n- eon_aurora: 7354\n terraBeta: 2965.69\n auroraDelta: ember\n deltaAurora: true\n eon_nova: 4647\n velox_nova: Terra\n dimensions:\n height_cm: 156.1\n width_cm: 110.4\n depth_cm: 48.3\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Nova\n - key: year\n value: 1911\n components:\n - name: Atlas\n qty: 4\n - name: Aurora\n qty: 2\n- omega_eon: ''\n betaGamma: 5477\n alpha_ember: 3276.45\n delta_omega: 9374.36\n alpha_terra: 4220\n atlasEmber: 4520\n gamma_lumen: gamma\n ember_terra: Atlas\n dimensions:\n height_cm: 263.4\n width_cm: 26.9\n depth_cm: 37.1\n flags:\n featured: true\n archived: true\n tags:\n - velox\n - zephyr\n - alpha\n - lumen\n meta:\n - key: origin\n value: Ember\n - key: year\n value: 1950\n notes: ''\n- terraBeta: ember\n auroraBeta: 2769.5\n zephyrAtlas: ''\n delta_ember: eon\n atlasGamma: Gamma\n atlasTerra: lumen\n dimensions:\n height_cm: 222.4\n width_cm: 203.2\n depth_cm: 57.7\n flags:\n featured: true\n archived: false\n components:\n - name: Velox\n qty: 3\n - name: Lumen\n qty: 4\n- novaVelox: 7348\n atlas_alpha: 4076\n velox_atlas: Atlas\n lumenEon: 7588\n beta_zephyr: 3696.9\n lumenNova: Omega\n dimensions:\n height_cm: 202.3\n width_cm: 129.6\n depth_cm: 32.7\n tags:\n - delta\n - terra\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 1980\n components:\n - name: Ember\n qty: 4\n - name: Terra\n qty: 2\n- gamma_lumen: Gamma\n deltaVelox: 4472\n aurora_nova: 2236\n eonOmega: 4898\n ember_lumen: 6134\n gamma_terra: 5379\n lumen_nova: Beta\n atlas_eon: false\n terraLumen: omega\n dimensions:\n height_cm: 24.5\n width_cm: 44.4\n depth_cm: 61.7\n flags:\n featured: false\n archived: false\n tags:\n - delta\n - delta\n - omega\n meta:\n - key: origin\n value: Atlas\n - key: year\n value: 1911\n components:\n - name: Delta\n qty: 1\n - name: Delta\n qty: 2",
"role": "assistant"
}
] |
merged_dedup_00061
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Reformat the XML below into YAML:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<student_assessment>\n<student>Mark Davis</student>\n<score>34</score>\n<grade>A</grade>\n</student_assessment>",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (student, score, grade) and a nesting depth of 1.\n2. Identify the target format requirements: YAML requires strict syntax. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nstudent: Mark Davis\nscore: 34\ngrade: A",
"role": "assistant"
}
] |
merged_dedup_00062
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML.",
"role": "system"
},
{
"content": "Output structured data for course_syllabus using TOML.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The course_syllabus should contain a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\ncourse = \"Compatible full-range analyzer\"\nweeks = 9\ncredits = 3",
"role": "assistant"
}
] |
merged_dedup_00063
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Output structured data for error_log using YAML.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The error_log should contain a dictionary with 3 root fields (timestamp, level, message) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\ntimestamp: '2026-01-22T04:03:05.882890'\nlevel: ERROR\nmessage: Themselves value medical each.",
"role": "assistant"
}
] |
merged_dedup_00064
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Reformat the XML below into CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>lori80</user>\n<rating>4</rating>\n<comment>Direction sign week represent thing friend art.</comment>\n<meta_info>\n<generated_at>2026-01-22T04:03:05.005015</generated_at>\n<version>v5.0</version>\n<tags>successful</tags>\n<tags>every</tags>\n<tags>still</tags>\n<tags>unit</tags>\n<tags>score</tags>\n</meta_info>\n<audit_log>\n<action>created</action>\n<by>fpowell</by>\n<timestamp>2024-12-06T01:40:04.096854</timestamp>\n</audit_log>\n<audit_log>\n<action>created</action>\n<by>kimberly73</by>\n<timestamp>1986-01-28T21:51:25.896323</timestamp>\n</audit_log>\n</customer_review>",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 5 root fields (user, rating, comment...) and a nesting depth of 3.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nuser,rating,comment,meta_info.generated_at,meta_info.version,meta_info.tags,audit_log\nlori80,4,Direction sign week represent thing friend art.,2026-01-22T04:03:05.005015,v5.0,\"[\"\"successful\"\", \"\"every\"\", \"\"still\"\", \"\"unit\"\", \"\"score\"\"]\",\"[{\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"fpowell\"\", \"\"timestamp\"\": \"\"2024-12-06T01:40:04.096854\"\"}, {\"\"action\"\": \"\"created\"\", \"\"by\"\": \"\"kimberly73\"\", \"\"timestamp\"\": \"\"1986-01-28T21:51:25.896323\"\"}]\"",
"role": "assistant"
}
] |
merged_dedup_00065
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\ndimensions.height_cm, dimensions.depth_cm, dimensions.width_cm, tags[0], eonLumen, eon_lumen, ember_delta, deltaBeta\nTEXT:\ndimensions.height_cm: 184.7 | dimensions.depth_cm: 96.0 | dimensions.width_cm: 66.0 | tags[0]: gamma | eonLumen: True | eon_lumen: 1324.71 | ember_delta: False | deltaBeta: 7067",
"role": "user"
},
{
"content": "dimensions:\n height_cm: 184.7\n depth_cm: 96.0\n width_cm: 66.0\ntags:\n- gamma\neonLumen: true\neon_lumen: 1324.71\nember_delta: false\ndeltaBeta: 7067",
"role": "assistant"
}
] |
merged_dedup_00066
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON.",
"role": "system"
},
{
"content": "Generate social media post data in JSON format.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\n{\n \"user\": \"moyerjohn\",\n \"post\": \"Team writer should. Democratic tree in doctor leg enter feeling stay.\",\n \"likes\": 135\n}",
"role": "assistant"
}
] |
merged_dedup_00067
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Output structured data for course_syllabus using CSV.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The course_syllabus should contain a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\ncourse,weeks,credits\nFace-to-face directional info-mediaries,9,3",
"role": "assistant"
}
] |
merged_dedup_00068
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.archived, dimensions.height_cm, tags[1], dimensions.depth_cm, atlasEmber, zephyrAlpha, betaAurora, velox_zephyr\nTEXT:\nflags.archived: False | dimensions.height_cm: 67.4 | tags[1]: terra | dimensions.depth_cm: 87.6 | atlasEmber: | zephyrAlpha: Omega | betaAurora: 1916 | velox_zephyr: True",
"role": "user"
},
{
"content": "atlasEmber = \"\"\nbetaAurora = 1916\nvelox_zephyr = true\nzephyrAlpha = \"Omega\"\ntags = [\"\", \"terra\"]\n[dimensions]\ndepth_cm = 87.6\nheight_cm = 67.4\n[flags]\narchived = false",
"role": "assistant"
}
] |
merged_dedup_00069
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\nflags.featured, dimensions.height_cm, dimensions.width_cm, flags.archived, eonZephyr, novaLumen, alpha_aurora, aurora_delta\nTEXT:\nflags.featured: False | dimensions.height_cm: 105.1 | dimensions.width_cm: 179.4 | flags.archived: False | eonZephyr: | novaLumen: 8526 | alpha_aurora: 3463.53 | aurora_delta: True",
"role": "user"
},
{
"content": "alpha_aurora = 3463.53\naurora_delta = true\neonZephyr = \"\"\nnovaLumen = 8526\n[dimensions]\nheight_cm = 105.1\nwidth_cm = 179.4\n[flags]\narchived = false\nfeatured = false",
"role": "assistant"
}
] |
merged_dedup_00070
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Output structured data for experiment_result using CSV.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The experiment_result should contain a dictionary with 4 root fields (experiment_id, title, metrics...) and a nesting depth of 2.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\nexperiment_id,title,metrics.accuracy,metrics.loss,metrics.epoch,config.batch_size,config.optimizer,config.lr\nEXP-548343,Analysis of special,0.9516,0.2734,49,64,sgd,0.001",
"role": "assistant"
}
] |
merged_dedup_00071
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Convert the following XML into YAML.\nConstraints:\n- Preserve original tag names exactly (no renaming to snake_case).\n- Child elements become mapping keys; repeated elements become lists.\n- Keep ordering and nesting as in XML.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nXML:\n<root><items><novaVelox>7889</novaVelox><beta_atlas>false</beta_atlas><terraNova>alpha</terraNova><gammaDelta>5865.94</gammaDelta><veloxGamma>Zephyr</veloxGamma><velox_velox>true</velox_velox><alpha_omega>664</alpha_omega><dimensions><height_cm>217.4</height_cm><width_cm>121.7</width_cm><depth_cm>90.3</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>aurora</tags><tags>atlas</tags><components><name>Lumen</name><qty>1</qty></components><components><name>Eon</name><qty>2</qty></components><notes /></items><items><gamma_terra>Lumen</gamma_terra><terra_lumen>true</terra_lumen><terra_atlas>5812</terra_atlas><velox_omega>1929</velox_omega><alphaVelox>3744.26</alphaVelox><omegaBeta>406.39</omegaBeta><delta_velox>3069</delta_velox><atlasAurora>true</atlasAurora><dimensions><height_cm>31.7</height_cm><width_cm>217.1</width_cm><depth_cm>10.1</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>eon</tags><tags>ember</tags><tags>ember</tags><tags>atlas</tags></items><items><omegaAlpha>eon</omegaAlpha><nova_gamma>true</nova_gamma><delta_atlas>7613.09</delta_atlas><terraLumen>atlas</terraLumen><gamma_ember>Alpha</gamma_ember><eon_alpha /><dimensions><height_cm>266.0</height_cm><width_cm>291.0</width_cm><depth_cm>55.2</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags></items><items><atlasBeta>Zephyr</atlasBeta><atlas_beta>gamma</atlas_beta><emberNova>velox</emberNova><terraGamma>8838.38</terraGamma><atlas_aurora>4413</atlas_aurora><gamma_terra>true</gamma_terra><nova_nova>eon</nova_nova><dimensions><height_cm>115.5</height_cm><width_cm>7.9</width_cm><depth_cm>61.5</depth_cm></dimensions><tags>atlas</tags><tags>lumen</tags><meta><key>origin</key><value>Omega</value></meta><meta><key>year</key><value>1945</value></meta><components><name>Gamma</name><qty>2</qty></components><components><name>Beta</name><qty>1</qty></components></items></root>",
"role": "user"
},
{
"content": "items:\n- novaVelox: 7889\n beta_atlas: false\n terraNova: alpha\n gammaDelta: 5865.94\n veloxGamma: Zephyr\n velox_velox: true\n alpha_omega: 664\n dimensions:\n height_cm: 217.4\n width_cm: 121.7\n depth_cm: 90.3\n flags:\n featured: true\n archived: false\n tags:\n - aurora\n - atlas\n components:\n - name: Lumen\n qty: 1\n - name: Eon\n qty: 2\n notes: ''\n- gamma_terra: Lumen\n terra_lumen: true\n terra_atlas: 5812\n velox_omega: 1929\n alphaVelox: 3744.26\n omegaBeta: 406.39\n delta_velox: 3069\n atlasAurora: true\n dimensions:\n height_cm: 31.7\n width_cm: 217.1\n depth_cm: 10.1\n flags:\n featured: false\n archived: true\n tags:\n - eon\n - ember\n - ember\n - atlas\n- omegaAlpha: eon\n nova_gamma: true\n delta_atlas: 7613.09\n terraLumen: atlas\n gamma_ember: Alpha\n eon_alpha: ''\n dimensions:\n height_cm: 266.0\n width_cm: 291.0\n depth_cm: 55.2\n flags:\n featured: false\n archived: false\n- atlasBeta: Zephyr\n atlas_beta: gamma\n emberNova: velox\n terraGamma: 8838.38\n atlas_aurora: 4413\n gamma_terra: true\n nova_nova: eon\n dimensions:\n height_cm: 115.5\n width_cm: 7.9\n depth_cm: 61.5\n tags:\n - atlas\n - lumen\n meta:\n - key: origin\n value: Omega\n - key: year\n value: 1945\n components:\n - name: Gamma\n qty: 2\n - name: Beta\n qty: 1",
"role": "assistant"
}
] |
merged_dedup_00072
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following JSON into well-formed XML.\nConstraints:\n- Use child elements only (no XML attributes).\n- Preserve key names and their letter case exactly.\n- Represent lists by repeating child elements in order.\nReturn ONLY XML.\nJSON:\n{\"items\": [{\"velox_atlas\": 3515.42, \"atlas_delta\": \"Ember\", \"zephyr_atlas\": \"Zephyr\", \"alphaLumen\": \"aurora\", \"zephyrAtlas\": \"terra\", \"beta_terra\": \"Ember\", \"beta_lumen\": 4229, \"ember_gamma\": \"\", \"velox_zephyr\": \"Delta\", \"flags\": {\"featured\": false, \"archived\": true}, \"tags\": [\"eon\", \"nova\", \"beta\"], \"components\": [{\"name\": \"Terra\", \"qty\": 2}, {\"name\": \"Beta\", \"qty\": 1}]}, {\"delta_atlas\": 1010, \"alpha_lumen\": 9253, \"omega_beta\": 1796, \"deltaEon\": \"beta\", \"velox_nova\": \"\", \"zephyr_gamma\": \"Alpha\", \"velox_lumen\": \"lumen\", \"dimensions\": {\"height_cm\": 205.0, \"width_cm\": 234.8, \"depth_cm\": 48.1}, \"tags\": [\"gamma\", \"atlas\", \"beta\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Beta\"}, {\"key\": \"year\", \"value\": 2014}]}, {\"alphaNova\": 5021.59, \"deltaAurora\": 8898.56, \"zephyrNova\": false, \"eonVelox\": true, \"veloxZephyr\": \"eon\", \"gamma_zephyr\": 2836, \"zephyr_nova\": 3087, \"dimensions\": {\"height_cm\": 123.1, \"width_cm\": 224.2, \"depth_cm\": 60.1}, \"flags\": {\"featured\": true, \"archived\": true}, \"tags\": [\"delta\", \"omega\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Nova\"}, {\"key\": \"year\", \"value\": 1940}]}, {\"aurora_atlas\": 943, \"velox_atlas\": 4200.24, \"ember_aurora\": \"Omega\", \"velox_aurora\": 3723, \"atlasDelta\": false, \"alpha_delta\": \"\", \"lumen_alpha\": 5888, \"gamma_velox\": \"delta\", \"dimensions\": {\"height_cm\": 207.0, \"width_cm\": 133.3, \"depth_cm\": 56.3}, \"flags\": {\"featured\": true, \"archived\": false}, \"tags\": [\"velox\", \"velox\", \"aurora\", \"terra\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Ember\"}, {\"key\": \"year\", \"value\": 1903}], \"components\": [{\"name\": \"Ember\", \"qty\": 1}, {\"name\": \"Lumen\", \"qty\": 3}]}, {\"lumen_ember\": \"omega\", \"lumenAurora\": false, \"delta_eon\": \"nova\", \"terra_zephyr\": 9484, \"zephyrAurora\": false, \"aurora_omega\": false, \"dimensions\": {\"height_cm\": 105.9, \"width_cm\": 34.8, \"depth_cm\": 75.1}, \"meta\": [{\"key\": \"origin\", \"value\": \"Omega\"}, {\"key\": \"year\", \"value\": 1974}], \"notes\": \"\"}]}",
"role": "user"
},
{
"content": "<root><items><velox_atlas>3515.42</velox_atlas><atlas_delta>Ember</atlas_delta><zephyr_atlas>Zephyr</zephyr_atlas><alphaLumen>aurora</alphaLumen><zephyrAtlas>terra</zephyrAtlas><beta_terra>Ember</beta_terra><beta_lumen>4229</beta_lumen><ember_gamma /><velox_zephyr>Delta</velox_zephyr><flags><featured>false</featured><archived>true</archived></flags><tags>eon</tags><tags>nova</tags><tags>beta</tags><components><name>Terra</name><qty>2</qty></components><components><name>Beta</name><qty>1</qty></components></items><items><delta_atlas>1010</delta_atlas><alpha_lumen>9253</alpha_lumen><omega_beta>1796</omega_beta><deltaEon>beta</deltaEon><velox_nova /><zephyr_gamma>Alpha</zephyr_gamma><velox_lumen>lumen</velox_lumen><dimensions><height_cm>205.0</height_cm><width_cm>234.8</width_cm><depth_cm>48.1</depth_cm></dimensions><tags>gamma</tags><tags>atlas</tags><tags>beta</tags><meta><key>origin</key><value>Beta</value></meta><meta><key>year</key><value>2014</value></meta></items><items><alphaNova>5021.59</alphaNova><deltaAurora>8898.56</deltaAurora><zephyrNova>false</zephyrNova><eonVelox>true</eonVelox><veloxZephyr>eon</veloxZephyr><gamma_zephyr>2836</gamma_zephyr><zephyr_nova>3087</zephyr_nova><dimensions><height_cm>123.1</height_cm><width_cm>224.2</width_cm><depth_cm>60.1</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>delta</tags><tags>omega</tags><meta><key>origin</key><value>Nova</value></meta><meta><key>year</key><value>1940</value></meta></items><items><aurora_atlas>943</aurora_atlas><velox_atlas>4200.24</velox_atlas><ember_aurora>Omega</ember_aurora><velox_aurora>3723</velox_aurora><atlasDelta>false</atlasDelta><alpha_delta /><lumen_alpha>5888</lumen_alpha><gamma_velox>delta</gamma_velox><dimensions><height_cm>207.0</height_cm><width_cm>133.3</width_cm><depth_cm>56.3</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>velox</tags><tags>velox</tags><tags>aurora</tags><tags>terra</tags><meta><key>origin</key><value>Ember</value></meta><meta><key>year</key><value>1903</value></meta><components><name>Ember</name><qty>1</qty></components><components><name>Lumen</name><qty>3</qty></components></items><items><lumen_ember>omega</lumen_ember><lumenAurora>false</lumenAurora><delta_eon>nova</delta_eon><terra_zephyr>9484</terra_zephyr><zephyrAurora>false</zephyrAurora><aurora_omega>false</aurora_omega><dimensions><height_cm>105.9</height_cm><width_cm>34.8</width_cm><depth_cm>75.1</depth_cm></dimensions><meta><key>origin</key><value>Omega</value></meta><meta><key>year</key><value>1974</value></meta><notes /></items></root>",
"role": "assistant"
}
] |
merged_dedup_00073
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following json into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nJSON:\n{\"items\": [{\"omega_atlas\": \"ember\", \"omega_lumen\": 3442, \"gammaAurora\": \"omega\", \"betaZephyr\": 4319.8, \"emberTerra\": \"Eon\", \"gamma_zephyr\": 7713.14, \"dimensions\": {\"height_cm\": 132.2, \"width_cm\": 58.7, \"depth_cm\": 77.9}, \"flags\": {\"featured\": false, \"archived\": true}, \"tags\": [\"eon\", \"zephyr\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Delta\"}, {\"key\": \"year\", \"value\": 1984}], \"components\": [{\"name\": \"Alpha\", \"qty\": 2}, {\"name\": \"Nova\", \"qty\": 5}]}, {\"lumenEon\": 1570.65, \"lumen_velox\": 5824.45, \"velox_gamma\": \"Beta\", \"terraLumen\": \"\", \"omegaBeta\": \"Velox\", \"lumen_ember\": true, \"delta_terra\": false, \"alphaDelta\": 7355, \"zephyrBeta\": \"gamma\", \"dimensions\": {\"height_cm\": 140.1, \"width_cm\": 120.0, \"depth_cm\": 79.1}, \"tags\": [\"terra\", \"zephyr\"], \"components\": [{\"name\": \"Eon\", \"qty\": 1}, {\"name\": \"Gamma\", \"qty\": 5}], \"notes\": \"\"}, {\"alpha_aurora\": true, \"emberEon\": \"aurora\", \"lumenEon\": false, \"novaOmega\": \"Zephyr\", \"deltaAtlas\": \"lumen\", \"deltaOmega\": \"omega\", \"dimensions\": {\"height_cm\": 283.4, \"width_cm\": 18.6, \"depth_cm\": 60.2}, \"flags\": {\"featured\": true, \"archived\": false}, \"tags\": [\"alpha\", \"delta\", \"lumen\", \"velox\"]}, {\"eon_beta\": 5154.18, \"lumen_gamma\": 7061, \"delta_aurora\": \"Zephyr\", \"eonNova\": \"Delta\", \"auroraLumen\": 9459, \"dimensions\": {\"height_cm\": 186.5, \"width_cm\": 275.6, \"depth_cm\": 49.1}, \"flags\": {\"featured\": false, \"archived\": false}, \"tags\": [\"terra\", \"ember\", \"omega\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Beta\"}, {\"key\": \"year\", \"value\": 1911}], \"components\": [{\"name\": \"Omega\", \"qty\": 3}, {\"name\": \"Lumen\", \"qty\": 2}]}, {\"nova_terra\": 629.57, \"beta_ember\": true, \"gammaGamma\": 7639.29, \"omega_gamma\": 2472.09, \"velox_eon\": \"nova\", \"beta_alpha\": \"alpha\", \"emberEon\": false, \"gammaTerra\": \"beta\", \"dimensions\": {\"height_cm\": 284.9, \"width_cm\": 250.1, \"depth_cm\": 7.6}, \"flags\": {\"featured\": false, \"archived\": false}, \"tags\": [\"delta\", \"zephyr\", \"beta\", \"atlas\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Delta\"}, {\"key\": \"year\", \"value\": 1904}], \"components\": [{\"name\": \"Alpha\", \"qty\": 4}, {\"name\": \"Gamma\", \"qty\": 3}]}]}",
"role": "user"
},
{
"content": "items:\n- omega_atlas: ember\n omega_lumen: 3442\n gammaAurora: omega\n betaZephyr: 4319.8\n emberTerra: Eon\n gamma_zephyr: 7713.14\n dimensions:\n height_cm: 132.2\n width_cm: 58.7\n depth_cm: 77.9\n flags:\n featured: false\n archived: true\n tags:\n - eon\n - zephyr\n meta:\n - key: origin\n value: Delta\n - key: year\n value: 1984\n components:\n - name: Alpha\n qty: 2\n - name: Nova\n qty: 5\n- lumenEon: 1570.65\n lumen_velox: 5824.45\n velox_gamma: Beta\n terraLumen: ''\n omegaBeta: Velox\n lumen_ember: true\n delta_terra: false\n alphaDelta: 7355\n zephyrBeta: gamma\n dimensions:\n height_cm: 140.1\n width_cm: 120.0\n depth_cm: 79.1\n tags:\n - terra\n - zephyr\n components:\n - name: Eon\n qty: 1\n - name: Gamma\n qty: 5\n notes: ''\n- alpha_aurora: true\n emberEon: aurora\n lumenEon: false\n novaOmega: Zephyr\n deltaAtlas: lumen\n deltaOmega: omega\n dimensions:\n height_cm: 283.4\n width_cm: 18.6\n depth_cm: 60.2\n flags:\n featured: true\n archived: false\n tags:\n - alpha\n - delta\n - lumen\n - velox\n- eon_beta: 5154.18\n lumen_gamma: 7061\n delta_aurora: Zephyr\n eonNova: Delta\n auroraLumen: 9459\n dimensions:\n height_cm: 186.5\n width_cm: 275.6\n depth_cm: 49.1\n flags:\n featured: false\n archived: false\n tags:\n - terra\n - ember\n - omega\n meta:\n - key: origin\n value: Beta\n - key: year\n value: 1911\n components:\n - name: Omega\n qty: 3\n - name: Lumen\n qty: 2\n- nova_terra: 629.57\n beta_ember: true\n gammaGamma: 7639.29\n omega_gamma: 2472.09\n velox_eon: nova\n beta_alpha: alpha\n emberEon: false\n gammaTerra: beta\n dimensions:\n height_cm: 284.9\n width_cm: 250.1\n depth_cm: 7.6\n flags:\n featured: false\n archived: false\n tags:\n - delta\n - zephyr\n - beta\n - atlas\n meta:\n - key: origin\n value: Delta\n - key: year\n value: 1904\n components:\n - name: Alpha\n qty: 4\n - name: Gamma\n qty: 3",
"role": "assistant"
}
] |
merged_dedup_00074
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following yaml into JSON.\nReturn ONLY JSON.\nYAML:\nitems:\n- omegaEmber: false\n alphaOmega: true\n lumen_alpha: Nova\n ember_terra: 3872\n auroraAlpha: alpha\n terraAurora: Delta\n atlasTerra: 2096.73\n gamma_nova: terra\n terraNova: zephyr\n dimensions:\n height_cm: 119.8\n width_cm: 165.6\n depth_cm: 89.2\n flags:\n featured: false\n archived: false\n tags:\n - beta\n - terra\n - lumen\n meta:\n - key: origin\n value: Ember\n - key: year\n value: 1969\n- alpha_zephyr: false\n zephyrGamma: 7456.73\n velox_atlas: Zephyr\n alphaTerra: 1749.44\n auroraBeta: omega\n aurora_velox: eon\n omega_omega: false\n dimensions:\n height_cm: 43.0\n width_cm: 217.7\n depth_cm: 29.5\n flags:\n featured: false\n archived: true\n tags:\n - omega\n - gamma\n - atlas\n - beta\n notes: ''\n- terra_velox: 2484.02\n velox_beta: ember\n veloxLumen: false\n eonZephyr: 7972\n terra_atlas: 2845\n dimensions:\n height_cm: 68.4\n width_cm: 295.8\n depth_cm: 58.4\n flags:\n featured: false\n archived: true\n meta:\n - key: origin\n value: Aurora\n - key: year\n value: 1943",
"role": "user"
},
{
"content": "{\"items\": [{\"omegaEmber\": false, \"alphaOmega\": true, \"lumen_alpha\": \"Nova\", \"ember_terra\": 3872, \"auroraAlpha\": \"alpha\", \"terraAurora\": \"Delta\", \"atlasTerra\": 2096.73, \"gamma_nova\": \"terra\", \"terraNova\": \"zephyr\", \"dimensions\": {\"height_cm\": 119.8, \"width_cm\": 165.6, \"depth_cm\": 89.2}, \"flags\": {\"featured\": false, \"archived\": false}, \"tags\": [\"beta\", \"terra\", \"lumen\"], \"meta\": [{\"key\": \"origin\", \"value\": \"Ember\"}, {\"key\": \"year\", \"value\": 1969}]}, {\"alpha_zephyr\": false, \"zephyrGamma\": 7456.73, \"velox_atlas\": \"Zephyr\", \"alphaTerra\": 1749.44, \"auroraBeta\": \"omega\", \"aurora_velox\": \"eon\", \"omega_omega\": false, \"dimensions\": {\"height_cm\": 43.0, \"width_cm\": 217.7, \"depth_cm\": 29.5}, \"flags\": {\"featured\": false, \"archived\": true}, \"tags\": [\"omega\", \"gamma\", \"atlas\", \"beta\"], \"notes\": \"\"}, {\"terra_velox\": 2484.02, \"velox_beta\": \"ember\", \"veloxLumen\": false, \"eonZephyr\": 7972, \"terra_atlas\": 2845, \"dimensions\": {\"height_cm\": 68.4, \"width_cm\": 295.8, \"depth_cm\": 58.4}, \"flags\": {\"featured\": false, \"archived\": true}, \"meta\": [{\"key\": \"origin\", \"value\": \"Aurora\"}, {\"key\": \"year\", \"value\": 1943}]}]}",
"role": "assistant"
}
] |
merged_dedup_00075
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following csv into XML.\nReturn ONLY XML.\nCSV:\nalphaVelox,alpha_alpha,alpha_lumen,alpha_omega,alpha_terra,alpha_zephyr,atlasAurora,auroraAurora,auroraNova,auroraVelox,betaGamma,components,deltaDelta,deltaEon,delta_zephyr,dimensions,emberBeta,emberLumen,ember_alpha,ember_beta,eonAurora,eon_terra,eon_zephyr,flags,gammaAurora,gammaEmber,gamma_lumen,meta,notes,novaAtlas,novaVelox,omegaEon,omega_gamma,tags,terra_terra,velox_beta,velox_delta,zephyrAlpha,zephyr_beta,zephyr_lumen\n,,,4008,true,atlas,,,true,,,\"[{\"\"name\"\": \"\"Atlas\"\", \"\"qty\"\": 1}, {\"\"name\"\": \"\"Zephyr\"\", \"\"qty\"\": 3}]\",,1557,,\"{\"\"height_cm\"\": 294.0, \"\"width_cm\"\": 54.1, \"\"depth_cm\"\": 7.4}\",,,6049.81,,,Ember,,\"{\"\"featured\"\": true, \"\"archived\"\": false}\",5542.39,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Terra\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2011}]\",,,,,,\"[\"\"atlas\"\", \"\"zephyr\"\"]\",,,false,,,\n,1291,eon,,,,,,,4386,,,,,,\"{\"\"height_cm\"\": 216.2, \"\"width_cm\"\": 154.3, \"\"depth_cm\"\": 56.5}\",1435,,,,eon,,2731,,,,9325.44,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Lumen\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1933}]\",,,,6748,,\"[\"\"omega\"\", \"\"atlas\"\", \"\"velox\"\"]\",false,,,,,\n,,,,,,,,,,8775.74,,904,,,\"{\"\"height_cm\"\": 115.8, \"\"width_cm\"\": 198.1, \"\"depth_cm\"\": 41.5}\",,6663,,false,,,,,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Eon\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1957}]\",,true,,,6614,,,true,,,5137.47,eon\n1555.88,,,,,,7929.81,7830.45,,,,\"[{\"\"name\"\": \"\"Aurora\"\", \"\"qty\"\": 3}, {\"\"name\"\": \"\"Delta\"\", \"\"qty\"\": 1}]\",,,4492,\"{\"\"height_cm\"\": 170.4, \"\"width_cm\"\": 283.5, \"\"depth_cm\"\": 75.3}\",,,,,,,,,,6299.98,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Lumen\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1934}]\",Beta,,Delta,,,\"[\"\"nova\"\", \"\"delta\"\", \"\"aurora\"\"]\",,,,8880.78,,",
"role": "user"
},
{
"content": "<items><items><alpha_terra>true</alpha_terra><alpha_zephyr>atlas</alpha_zephyr><velox_delta>false</velox_delta><eon_terra>Ember</eon_terra><ember_alpha>6049.81</ember_alpha><deltaEon>1557</deltaEon><alpha_omega>4008</alpha_omega><gammaAurora>5542.39</gammaAurora><auroraNova>true</auroraNova><dimensions><height_cm>294.0</height_cm><width_cm>54.1</width_cm><depth_cm>7.4</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>atlas</tags><tags>zephyr</tags><meta><key>origin</key><value>Terra</value></meta><meta><key>year</key><value>2011</value></meta><components><name>Atlas</name><qty>1</qty></components><components><name>Zephyr</name><qty>3</qty></components></items><items><gamma_lumen>9325.44</gamma_lumen><terra_terra>false</terra_terra><eonAurora>eon</eonAurora><eon_zephyr>2731</eon_zephyr><emberBeta>1435</emberBeta><alpha_lumen>eon</alpha_lumen><auroraVelox>4386</auroraVelox><omegaEon>6748</omegaEon><alpha_alpha>1291</alpha_alpha><dimensions><height_cm>216.2</height_cm><width_cm>154.3</width_cm><depth_cm>56.5</depth_cm></dimensions><tags>omega</tags><tags>atlas</tags><tags>velox</tags><meta><key>origin</key><value>Lumen</value></meta><meta><key>year</key><value>1933</value></meta></items><items><emberLumen>6663</emberLumen><deltaDelta>904</deltaDelta><novaAtlas>true</novaAtlas><betaGamma>8775.74</betaGamma><ember_beta>false</ember_beta><zephyr_beta>5137.47</zephyr_beta><velox_beta>true</velox_beta><omega_gamma>6614</omega_gamma><zephyr_lumen>eon</zephyr_lumen><dimensions><height_cm>115.8</height_cm><width_cm>198.1</width_cm><depth_cm>41.5</depth_cm></dimensions><meta><key>origin</key><value>Eon</value></meta><meta><key>year</key><value>1957</value></meta></items><items><novaVelox>Delta</novaVelox><alphaVelox>1555.88</alphaVelox><delta_zephyr>4492</delta_zephyr><auroraAurora>7830.45</auroraAurora><atlasAurora>7929.81</atlasAurora><zephyrAlpha>8880.78</zephyrAlpha><gammaEmber>6299.98</gammaEmber><dimensions><height_cm>170.4</height_cm><width_cm>283.5</width_cm><depth_cm>75.3</depth_cm></dimensions><tags>nova</tags><tags>delta</tags><tags>aurora</tags><meta><key>origin</key><value>Lumen</value></meta><meta><key>year</key><value>1934</value></meta><components><name>Aurora</name><qty>3</qty></components><components><name>Delta</name><qty>1</qty></components><notes>Beta</notes></items></items>",
"role": "assistant"
}
] |
merged_dedup_00076
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in JSON format. Analyze the data structure and generate syntactically perfect JSON.",
"role": "system"
},
{
"content": "Generate research paper data in JSON format.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The research_paper should contain a dictionary with 6 root fields (paper_id, title, authors...) and a nesting depth of 3.\n2. Select the format: JSON is chosen. Ensure all keys are quoted and nested structures use curly braces.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\n{\n \"paper_id\": \"arXiv:2020.70770\",\n \"title\": \"Stand-alone needs-based standardization\",\n \"authors\": [\n {\n \"name\": \"Michael Deleon\",\n \"affiliation\": \"Thomas Inc\",\n \"email\": \"richard73@example.com\"\n },\n {\n \"name\": \"Laurie Torres\",\n \"affiliation\": \"Gross Ltd\",\n \"email\": \"zunigawendy@example.org\"\n },\n {\n \"name\": \"Jasmin Mcdonald\",\n \"affiliation\": \"Obrien-Day\",\n \"email\": \"stacie24@example.com\"\n }\n ],\n \"abstract\": \"Policy someone thank company book. Once same nation charge every.\\nStudent game by event.\",\n \"keywords\": [\n \"say\",\n \"adult\",\n \"other\",\n \"yet\"\n ],\n \"publication\": {\n \"venue\": \"Nature\",\n \"year\": 2024,\n \"doi\": \"10.7430/lhxI\"\n }\n}",
"role": "assistant"
}
] |
merged_dedup_00077
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following csv into YAML.\nConstraints:\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys under the item by 2 more spaces.\nReturn ONLY YAML.\nCSV:\natlasEon,atlasNova,atlasOmega,atlas_gamma,auroraAlpha,auroraLumen,aurora_alpha,aurora_aurora,aurora_ember,aurora_eon,aurora_gamma,betaAtlas,betaDelta,components,deltaAtlas,delta_aurora,dimensions,emberLumen,eonLumen,eon_eon,eon_gamma,eon_lumen,flags,gamma_atlas,gamma_aurora,lumenAlpha,lumenEmber,meta,notes,novaEmber,novaGamma,nova_terra,nova_zephyr,omegaZephyr,omega_omega,omega_terra,tags,terraGamma,zephyrAtlas,zephyrAurora\n,,,,,,,1180,,,,,,\"[{\"\"name\"\": \"\"Velox\"\", \"\"qty\"\": 1}, {\"\"name\"\": \"\"Terra\"\", \"\"qty\"\": 3}]\",,,\"{\"\"height_cm\"\": 241.4, \"\"width_cm\"\": 28.6, \"\"depth_cm\"\": 83.5}\",,7897,,Aurora,,\"{\"\"featured\"\": false, \"\"archived\"\": false}\",,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Terra\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2007}]\",,,,true,55,,,2750,\"[\"\"delta\"\", \"\"nova\"\"]\",6860.69,,\nfalse,,Lumen,,,,,,,nova,2910,,6494,,,,\"{\"\"height_cm\"\": 295.3, \"\"width_cm\"\": 156.8, \"\"depth_cm\"\": 83.3}\",Alpha,,9069.77,,,\"{\"\"featured\"\": true, \"\"archived\"\": true}\",,,,,,,,,,,,5754,,\"[\"\"gamma\"\", \"\"zephyr\"\"]\",,2466,\n,Velox,,,,,,,,,,,,\"[{\"\"name\"\": \"\"Gamma\"\", \"\"qty\"\": 5}, {\"\"name\"\": \"\"Delta\"\", \"\"qty\"\": 3}]\",6481.88,Zephyr,\"{\"\"height_cm\"\": 137.4, \"\"width_cm\"\": 170.7, \"\"depth_cm\"\": 1.0}\",,,,,2682.82,\"{\"\"featured\"\": true, \"\"archived\"\": false}\",,,false,Omega,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Omega\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1997}]\",Zephyr,nova,1203,,,,,,,,,false\n,,,7398.34,Zephyr,4771,Aurora,,4899.52,,,3947,,,,,\"{\"\"height_cm\"\": 83.8, \"\"width_cm\"\": 29.4, \"\"depth_cm\"\": 11.2}\",,,,,,\"{\"\"featured\"\": true, \"\"archived\"\": false}\",Velox,Alpha,,,,,,,,,false,,,\"[\"\"lumen\"\", \"\"nova\"\", \"\"eon\"\"]\",,,",
"role": "user"
},
{
"content": "items:\n- aurora_aurora: 1180\n omega_terra: 2750\n eonLumen: 7897\n terraGamma: 6860.69\n nova_terra: true\n eon_gamma: Aurora\n nova_zephyr: 55\n dimensions:\n height_cm: 241.4\n width_cm: 28.6\n depth_cm: 83.5\n flags:\n featured: false\n archived: false\n tags:\n - delta\n - nova\n meta:\n - key: origin\n value: Terra\n - key: year\n value: 2007\n components:\n - name: Velox\n qty: 1\n - name: Terra\n qty: 3\n- aurora_gamma: 2910\n eon_eon: 9069.77\n omega_omega: 5754\n emberLumen: Alpha\n aurora_eon: nova\n atlasEon: false\n atlasOmega: Lumen\n zephyrAtlas: 2466\n betaDelta: 6494\n dimensions:\n height_cm: 295.3\n width_cm: 156.8\n depth_cm: 83.3\n flags:\n featured: true\n archived: true\n tags:\n - gamma\n - zephyr\n- eon_lumen: 2682.82\n lumenAlpha: false\n zephyrAurora: false\n delta_aurora: Zephyr\n atlasNova: Velox\n novaGamma: 1203\n deltaAtlas: 6481.88\n novaEmber: nova\n lumenEmber: Omega\n dimensions:\n height_cm: 137.4\n width_cm: 170.7\n depth_cm: 1.0\n flags:\n featured: true\n archived: false\n meta:\n - key: origin\n value: Omega\n - key: year\n value: 1997\n components:\n - name: Gamma\n qty: 5\n - name: Delta\n qty: 3\n notes: Zephyr\n- atlas_gamma: 7398.34\n betaAtlas: 3947\n aurora_alpha: Aurora\n auroraLumen: 4771\n aurora_ember: 4899.52\n auroraAlpha: Zephyr\n gamma_aurora: Alpha\n omegaZephyr: false\n gamma_atlas: Velox\n dimensions:\n height_cm: 83.8\n width_cm: 29.4\n depth_cm: 11.2\n flags:\n featured: true\n archived: false\n tags:\n - lumen\n - nova\n - eon",
"role": "assistant"
}
] |
merged_dedup_00078
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ntags[0], dimensions.width_cm, tags[1], dimensions.depth_cm, gammaDelta, omega_eon, betaDelta, atlasZephyr\nTEXT:\ntags[0]: alpha | dimensions.width_cm: 81.4 | tags[1]: alpha | dimensions.depth_cm: 14.7 | gammaDelta: | omega_eon: Omega | betaDelta: Terra | atlasZephyr: delta",
"role": "user"
},
{
"content": "atlasZephyr = \"delta\"\nbetaDelta = \"Terra\"\ngammaDelta = \"\"\nomega_eon = \"Omega\"\ntags = [\"alpha\", \"alpha\"]\n[dimensions]\ndepth_cm = 14.7\nwidth_cm = 81.4",
"role": "assistant"
}
] |
merged_dedup_00079
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Transform this data from XML to CSV:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<customer_review>\n<user>mcbridedennis</user>\n<rating>4</rating>\n<comment>Now through hospital one.</comment>\n</customer_review>",
"role": "user"
},
{
"content": "Approach:\n1. Analyze the input XML structure: It represents a dictionary with 3 root fields (user, rating, comment) and a nesting depth of 1.\n2. Identify the target format requirements: CSV requires strict syntax. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Map the fields: The root keys will map directly, while nested objects need careful formatting.\n4. Handle data types: Ensure strings, numbers, and booleans are formatted correctly for the target.\n5. Construct the output: serialized the data strictly following the target schema.\nOutput:\nuser,rating,comment\nmcbridedennis,4,Now through hospital one.",
"role": "assistant"
}
] |
merged_dedup_00080
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Convert the following XML into YAML.\nConstraints:\n- Preserve original tag names exactly (no renaming to snake_case).\n- Child elements become mapping keys; repeated elements become lists.\n- Keep ordering and nesting as in XML.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nXML:\n<root><items><lumen_atlas>7394</lumen_atlas><atlasBeta>6030.72</atlasBeta><gammaNova /><deltaBeta>Omega</deltaBeta><atlasEon>eon</atlasEon><betaLumen>beta</betaLumen><terraDelta>1399.16</terraDelta><dimensions><height_cm>117.0</height_cm><width_cm>58.2</width_cm><depth_cm>85.0</depth_cm></dimensions><tags>zephyr</tags><tags>nova</tags><components><name>Eon</name><qty>3</qty></components><components><name>Atlas</name><qty>4</qty></components></items><items><ember_beta>7329.78</ember_beta><delta_lumen>Omega</delta_lumen><ember_velox>629</ember_velox><terraOmega>false</terraOmega><velox_terra>Aurora</velox_terra><dimensions><height_cm>173.3</height_cm><width_cm>133.7</width_cm><depth_cm>99.4</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><tags>lumen</tags><tags>nova</tags><tags>nova</tags><meta><key>origin</key><value>Alpha</value></meta><meta><key>year</key><value>2009</value></meta><notes /></items><items><alpha_aurora>1642.22</alpha_aurora><terraAtlas>1705</terraAtlas><atlasEon>aurora</atlasEon><ember_omega>beta</ember_omega><emberTerra>false</emberTerra><alpha_lumen>1793</alpha_lumen><eonVelox>false</eonVelox><beta_lumen>eon</beta_lumen><ember_beta>2891.59</ember_beta><dimensions><height_cm>101.1</height_cm><width_cm>194.7</width_cm><depth_cm>57.3</depth_cm></dimensions><flags><featured>false</featured><archived>false</archived></flags><tags>zephyr</tags><tags>nova</tags><tags>nova</tags><tags>nova</tags><meta><key>origin</key><value>Omega</value></meta><meta><key>year</key><value>1983</value></meta><components><name>Velox</name><qty>2</qty></components><components><name>Nova</name><qty>1</qty></components><notes /></items><items><gammaLumen>8442</gammaLumen><delta_ember>9672.98</delta_ember><veloxOmega>true</veloxOmega><atlasGamma>332.24</atlasGamma><lumen_lumen>5097</lumen_lumen><gammaVelox>5650.64</gammaVelox><atlas_velox>Zephyr</atlas_velox><alphaTerra>6109</alphaTerra><dimensions><height_cm>158.3</height_cm><width_cm>30.7</width_cm><depth_cm>61.5</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>delta</tags><tags>gamma</tags><tags>omega</tags><tags>delta</tags><meta><key>origin</key><value>Lumen</value></meta><meta><key>year</key><value>1983</value></meta><components><name>Eon</name><qty>1</qty></components><components><name>Eon</name><qty>3</qty></components><notes>Gamma</notes></items></root>",
"role": "user"
},
{
"content": "items:\n- lumen_atlas: 7394\n atlasBeta: 6030.72\n gammaNova: ''\n deltaBeta: Omega\n atlasEon: eon\n betaLumen: beta\n terraDelta: 1399.16\n dimensions:\n height_cm: 117.0\n width_cm: 58.2\n depth_cm: 85.0\n tags:\n - zephyr\n - nova\n components:\n - name: Eon\n qty: 3\n - name: Atlas\n qty: 4\n- ember_beta: 7329.78\n delta_lumen: Omega\n ember_velox: 629\n terraOmega: false\n velox_terra: Aurora\n dimensions:\n height_cm: 173.3\n width_cm: 133.7\n depth_cm: 99.4\n flags:\n featured: false\n archived: false\n tags:\n - lumen\n - nova\n - nova\n meta:\n - key: origin\n value: Alpha\n - key: year\n value: 2009\n notes: ''\n- alpha_aurora: 1642.22\n terraAtlas: 1705\n atlasEon: aurora\n ember_omega: beta\n emberTerra: false\n alpha_lumen: 1793\n eonVelox: false\n beta_lumen: eon\n ember_beta: 2891.59\n dimensions:\n height_cm: 101.1\n width_cm: 194.7\n depth_cm: 57.3\n flags:\n featured: false\n archived: false\n tags:\n - zephyr\n - nova\n - nova\n - nova\n meta:\n - key: origin\n value: Omega\n - key: year\n value: 1983\n components:\n - name: Velox\n qty: 2\n - name: Nova\n qty: 1\n notes: ''\n- gammaLumen: 8442\n delta_ember: 9672.98\n veloxOmega: true\n atlasGamma: 332.24\n lumen_lumen: 5097\n gammaVelox: 5650.64\n atlas_velox: Zephyr\n alphaTerra: 6109\n dimensions:\n height_cm: 158.3\n width_cm: 30.7\n depth_cm: 61.5\n flags:\n featured: true\n archived: false\n tags:\n - delta\n - gamma\n - omega\n - delta\n meta:\n - key: origin\n value: Lumen\n - key: year\n value: 1983\n components:\n - name: Eon\n qty: 1\n - name: Eon\n qty: 3\n notes: Gamma",
"role": "assistant"
}
] |
merged_dedup_00081
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML.",
"role": "system"
},
{
"content": "Output structured data for financial_report using TOML.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The financial_report should contain a dictionary with 3 root fields (company, revenue, profit) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\ncompany = \"Fisher Ltd\"\nrevenue = 162202\nprofit = 69226",
"role": "assistant"
}
] |
merged_dedup_00082
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in CSV format. Analyze the data structure and generate syntactically perfect CSV.",
"role": "system"
},
{
"content": "Generate course syllabus data in CSV format.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The course_syllabus should contain a dictionary with 3 root fields (course, weeks, credits) and a nesting depth of 1.\n2. Select the format: CSV is chosen. Flatten the hierarchical structure. Use dot notation for nested keys in the header.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\ncourse,weeks,credits\nMulti-layered local interface,12,3",
"role": "assistant"
}
] |
merged_dedup_00083
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in TOML format. Analyze the data structure and generate syntactically perfect TOML.",
"role": "system"
},
{
"content": "Create a TOML representation of sales analytics.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The sales_analytics should contain a dictionary with 3 root fields (period, sales, region) and a nesting depth of 1.\n2. Select the format: TOML is chosen. Define hierarchy using dot-notation or [section] headers.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\nperiod = \"Q1\"\nsales = 2571\nregion = \"Cranetown\"",
"role": "assistant"
}
] |
merged_dedup_00084
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output YAML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nATTRIBUTES:\ntags[0], dimensions.height_cm, flags.archived, flags.featured, betaEmber, eonLumen, terra_gamma, alpha_ember\nTEXT:\ntags[0]: nova | dimensions.height_cm: 254.7 | flags.archived: True | flags.featured: False | betaEmber: 2658 | eonLumen: 4519.77 | terra_gamma: ember | alpha_ember: True",
"role": "user"
},
{
"content": "tags:\n- nova\ndimensions:\n height_cm: 254.7\nflags:\n archived: true\n featured: false\nbetaEmber: 2658\neonLumen: 4519.77\nterra_gamma: ember\nalpha_ember: true",
"role": "assistant"
}
] |
merged_dedup_00085
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in YAML format. Analyze the data structure and generate syntactically perfect YAML.",
"role": "system"
},
{
"content": "Create a YAML representation of social media post.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The social_media_post should contain a dictionary with 3 root fields (user, post, likes) and a nesting depth of 1.\n2. Select the format: YAML is chosen. Use indentation to represent nesting. lists are denoted by hyphens.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\nuser: james92\npost: Two final modern open image room. Arrive live about hear front all. Available\n effort alone.\nlikes: 864",
"role": "assistant"
}
] |
merged_dedup_00086
|
daichira/structured-hard-sft-4k
|
[
{
"content": "Extract the following attributes from text and output TOML.\nConstraints:\n- Output ONLY the requested attributes (no extra keys).\n- Preserve key paths and nesting exactly as specified.\n- Use dotted tables and arrays-of-tables to represent nested objects and lists.\n- Do NOT use TOML inline tables (curly braces like { ... }).\n- Align keys directly under their [table] headers; avoid arbitrary indentation.\n- Do NOT wrap values in JSON/HCL-style objects. Use [tables] / [[tables]] only.\nReturn ONLY TOML.\nATTRIBUTES:\ndimensions.height_cm, flags.featured, flags.archived, tags[1], notes, gamma_lumen, delta_delta, emberAlpha\nTEXT:\ndimensions.height_cm: 10.8 | flags.featured: False | flags.archived: False | tags[1]: delta | notes: | gamma_lumen: | delta_delta: 3399.84 | emberAlpha: lumen",
"role": "user"
},
{
"content": "delta_delta = 3399.84\nemberAlpha = \"lumen\"\ngamma_lumen = \"\"\nnotes = \"\"\ntags = [\"\", \"delta\"]\n[dimensions]\nheight_cm = 10.8\n[flags]\narchived = false\nfeatured = false",
"role": "assistant"
}
] |
merged_dedup_00087
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following csv into XML.\nReturn ONLY XML.\nCSV:\nalpha_alpha,atlasGamma,atlas_delta,aurora_nova,beta_nova,components,delta_zephyr,dimensions,eonDelta,eonTerra,flags,gammaAlpha,gammaAurora,gamma_alpha,gamma_eon,lumenAlpha,lumen_alpha,meta,notes,nova_ember,omegaEon,omegaVelox,omega_gamma,tags,terraNova,terraOmega,terra_delta,veloxDelta,veloxEon,velox_lumen,zephyrNova\n,,false,,Lumen,\"[{\"\"name\"\": \"\"Ember\"\", \"\"qty\"\": 2}, {\"\"name\"\": \"\"Beta\"\", \"\"qty\"\": 4}]\",,\"{\"\"height_cm\"\": 217.5, \"\"width_cm\"\": 120.5, \"\"depth_cm\"\": 18.5}\",,true,\"{\"\"featured\"\": true, \"\"archived\"\": true}\",,,,2479,Lumen,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Alpha\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2022}]\",Terra,,,,,\"[\"\"terra\"\", \"\"gamma\"\", \"\"atlas\"\"]\",,false,,,,,\n4134.13,,,Beta,,\"[{\"\"name\"\": \"\"Ember\"\", \"\"qty\"\": 5}, {\"\"name\"\": \"\"Lumen\"\", \"\"qty\"\": 1}]\",,\"{\"\"height_cm\"\": 266.3, \"\"width_cm\"\": 239.9, \"\"depth_cm\"\": 9.7}\",lumen,,\"{\"\"featured\"\": true, \"\"archived\"\": false}\",,nova,,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Lumen\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1913}]\",,,,true,,\"[\"\"eon\"\", \"\"atlas\"\", \"\"terra\"\", \"\"terra\"\"]\",,,1123,,,,\n,false,,,,\"[{\"\"name\"\": \"\"Zephyr\"\", \"\"qty\"\": 5}, {\"\"name\"\": \"\"Velox\"\", \"\"qty\"\": 3}]\",,\"{\"\"height_cm\"\": 251.9, \"\"width_cm\"\": 223.5, \"\"depth_cm\"\": 59.4}\",,,,,,,,,false,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Zephyr\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 1906}]\",,,,,,\"[\"\"lumen\"\", \"\"lumen\"\", \"\"lumen\"\", \"\"delta\"\"]\",4636,,,,2078,Velox,\n,,,,,,538.1,\"{\"\"height_cm\"\": 119.0, \"\"width_cm\"\": 239.1, \"\"depth_cm\"\": 62.1}\",,8867.67,\"{\"\"featured\"\": false, \"\"archived\"\": true}\",4578.58,,,,,,\"[{\"\"key\"\": \"\"origin\"\", \"\"value\"\": \"\"Atlas\"\"}, {\"\"key\"\": \"\"year\"\", \"\"value\"\": 2018}]\",,zephyr,Terra,,3800,\"[\"\"gamma\"\", \"\"zephyr\"\", \"\"nova\"\"]\",,,,46.69,,,",
"role": "user"
},
{
"content": "<items><items><lumenAlpha>Lumen</lumenAlpha><gamma_eon>2479</gamma_eon><gamma_alpha /><beta_nova>Lumen</beta_nova><atlas_delta>false</atlas_delta><eonTerra>true</eonTerra><terraOmega>false</terraOmega><zephyrNova /><dimensions><height_cm>217.5</height_cm><width_cm>120.5</width_cm><depth_cm>18.5</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>terra</tags><tags>gamma</tags><tags>atlas</tags><meta><key>origin</key><value>Alpha</value></meta><meta><key>year</key><value>2022</value></meta><components><name>Ember</name><qty>2</qty></components><components><name>Beta</name><qty>4</qty></components><notes>Terra</notes></items><items><eonDelta>lumen</eonDelta><terra_delta>1123</terra_delta><omegaVelox>true</omegaVelox><alpha_alpha>4134.13</alpha_alpha><aurora_nova>Beta</aurora_nova><gammaAurora>nova</gammaAurora><dimensions><height_cm>266.3</height_cm><width_cm>239.9</width_cm><depth_cm>9.7</depth_cm></dimensions><flags><featured>true</featured><archived>false</archived></flags><tags>eon</tags><tags>atlas</tags><tags>terra</tags><tags>terra</tags><meta><key>origin</key><value>Lumen</value></meta><meta><key>year</key><value>1913</value></meta><components><name>Ember</name><qty>5</qty></components><components><name>Lumen</name><qty>1</qty></components></items><items><lumen_alpha>false</lumen_alpha><veloxEon>2078</veloxEon><terraNova>4636</terraNova><atlasGamma>false</atlasGamma><velox_lumen>Velox</velox_lumen><dimensions><height_cm>251.9</height_cm><width_cm>223.5</width_cm><depth_cm>59.4</depth_cm></dimensions><tags>lumen</tags><tags>lumen</tags><tags>lumen</tags><tags>delta</tags><meta><key>origin</key><value>Zephyr</value></meta><meta><key>year</key><value>1906</value></meta><components><name>Zephyr</name><qty>5</qty></components><components><name>Velox</name><qty>3</qty></components></items><items><eonTerra>8867.67</eonTerra><delta_zephyr>538.1</delta_zephyr><veloxDelta>46.69</veloxDelta><omega_gamma>3800</omega_gamma><gammaAlpha>4578.58</gammaAlpha><omegaEon>Terra</omegaEon><nova_ember>zephyr</nova_ember><dimensions><height_cm>119.0</height_cm><width_cm>239.1</width_cm><depth_cm>62.1</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>gamma</tags><tags>zephyr</tags><tags>nova</tags><meta><key>origin</key><value>Atlas</value></meta><meta><key>year</key><value>2018</value></meta></items></items>",
"role": "assistant"
}
] |
merged_dedup_00088
|
u-10bei/structured_data_with_cot_dataset_512_v4
|
[
{
"content": "You are an expert in XML format. Analyze the data structure and generate syntactically perfect XML.",
"role": "system"
},
{
"content": "Create a XML representation of news article.",
"role": "user"
},
{
"content": "Approach:\n1. Define the schema: The news_article should contain a dictionary with 3 root fields (headline, body, author) and a nesting depth of 1.\n2. Select the format: XML is chosen. Map dictionary keys to tags. Handle list items by repeating child tags.\n3. Generate realistic content: Use plausible names, dates, and values appropriate for the domain.\n4. Structure the data: Organize the fields logically with appropriate nesting and hierarchies.\n5. Serialize: Output the final string making sure to escape special characters if necessary.\nOutput:\n<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<news_article>\n<headline>Republican respond individual town east.</headline>\n<body>Appear religious Republican member from store. Store note benefit spring ask key energy. House identify back.\nMy seek suggest care movement anyone. Difference control perform good.</body>\n<author>Tommy Porter</author>\n</news_article>",
"role": "assistant"
}
] |
merged_dedup_00089
|
daichira/structured-5k-mix-sft
|
[
{
"content": "Convert the following XML into YAML.\nConstraints:\n- Preserve original tag names exactly (no renaming to snake_case).\n- Child elements become mapping keys; repeated elements become lists.\n- Keep ordering and nesting as in XML.\n- Use 2-space indentation (no tabs). For sequences, start items with '- ' and indent child keys by 2 more spaces under the item.\nReturn ONLY YAML.\nXML:\n<root><items><omegaGamma>true</omegaGamma><zephyr_terra>false</zephyr_terra><zephyrEon>3555.03</zephyrEon><zephyr_zephyr>false</zephyr_zephyr><emberAurora>terra</emberAurora><dimensions><height_cm>257.9</height_cm><width_cm>116.7</width_cm><depth_cm>5.5</depth_cm></dimensions><flags><featured>true</featured><archived>true</archived></flags><tags>aurora</tags><tags>aurora</tags><tags>ember</tags><tags>ember</tags><meta><key>origin</key><value>Terra</value></meta><meta><key>year</key><value>2006</value></meta></items><items><velox_alpha>6359</velox_alpha><emberAtlas>false</emberAtlas><ember_omega /><emberAurora>14</emberAurora><atlas_atlas>false</atlas_atlas><auroraAurora>200.84</auroraAurora><delta_delta>9063.61</delta_delta><dimensions><height_cm>169.7</height_cm><width_cm>173.9</width_cm><depth_cm>35.7</depth_cm></dimensions><flags><featured>false</featured><archived>true</archived></flags><tags>velox</tags><tags>eon</tags><tags>nova</tags><tags>ember</tags><meta><key>origin</key><value>Delta</value></meta><meta><key>year</key><value>1918</value></meta><components><name>Delta</name><qty>2</qty></components><components><name>Eon</name><qty>3</qty></components></items><items><aurora_atlas>Alpha</aurora_atlas><omega_atlas>4509</omega_atlas><gamma_gamma /><eonVelox>omega</eonVelox><terra_omega>atlas</terra_omega><zephyr_alpha>4076.03</zephyr_alpha><terra_eon>beta</terra_eon><alpha_nova>nova</alpha_nova><terraEmber>false</terraEmber><flags><featured>false</featured><archived>true</archived></flags><tags>omega</tags><tags>terra</tags><meta><key>origin</key><value>Velox</value></meta><meta><key>year</key><value>1963</value></meta><components><name>Omega</name><qty>1</qty></components><components><name>Delta</name><qty>2</qty></components></items></root>",
"role": "user"
},
{
"content": "items:\n- omegaGamma: true\n zephyr_terra: false\n zephyrEon: 3555.03\n zephyr_zephyr: false\n emberAurora: terra\n dimensions:\n height_cm: 257.9\n width_cm: 116.7\n depth_cm: 5.5\n flags:\n featured: true\n archived: true\n tags:\n - aurora\n - aurora\n - ember\n - ember\n meta:\n - key: origin\n value: Terra\n - key: year\n value: 2006\n- velox_alpha: 6359\n emberAtlas: false\n ember_omega: ''\n emberAurora: 14\n atlas_atlas: false\n auroraAurora: 200.84\n delta_delta: 9063.61\n dimensions:\n height_cm: 169.7\n width_cm: 173.9\n depth_cm: 35.7\n flags:\n featured: false\n archived: true\n tags:\n - velox\n - eon\n - nova\n - ember\n meta:\n - key: origin\n value: Delta\n - key: year\n value: 1918\n components:\n - name: Delta\n qty: 2\n - name: Eon\n qty: 3\n- aurora_atlas: Alpha\n omega_atlas: 4509\n gamma_gamma: ''\n eonVelox: omega\n terra_omega: atlas\n zephyr_alpha: 4076.03\n terra_eon: beta\n alpha_nova: nova\n terraEmber: false\n flags:\n featured: false\n archived: true\n tags:\n - omega\n - terra\n meta:\n - key: origin\n value: Velox\n - key: year\n value: 1963\n components:\n - name: Omega\n qty: 1\n - name: Delta\n qty: 2",
"role": "assistant"
}
] |
merged_dedup_00090
|
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