| name: system-one-datasets |
| description: Typed-decision datasets for System One models, normalized to the /v1/systemone wire format |
| format: JSON Lines, one row per line, at <suite>/<config>/<split>.jsonl. state, question, and soft_label are JSON-encoded |
| strings (soft_label is the text 'null' when absent); every other field is a plain JSON value. |
| row_fields: |
| - id |
| - suite |
| - config |
| - kind |
| - state |
| - question |
| - options |
| - label |
| - soft_label |
| - source |
| - source_revision |
| - upstream |
| - license |
| wire_request: '{''state'': json.loads(row[''state'']), ''model'': <model>, ''questions'': {<any id>: json.loads(row[''question''])}}' |
| rebuild: uv run python -m system_one_datasets build --out data/ |
| validate: uv run python -m system_one_datasets validate data/ |
| configs: |
| - config: civil_comments |
| suite: moderation |
| kinds: |
| - noul |
| description: Is this online comment toxic? Soft label = share of annotators who said yes. |
| splits: |
| test: |
| file: moderation/civil_comments/test.jsonl |
| rows: 2000 |
| rows_with_soft_label: 2000 |
| sha256: ad73dc3e56fce9cfb7311268230e2935e355eb9d9f44f32acdb0b7e7bfb8ea6a |
| validation: |
| file: moderation/civil_comments/validation.jsonl |
| rows: 500 |
| rows_with_soft_label: 500 |
| sha256: 51663b5d1ad61149562bb50ad1f55714216fa7937ebda8e1a7a7503badea73ba |
| source: |
| hf_id: Praveenrajus/jev-bench |
| hf_config: civil_comments |
| revision: 18f88da81c28c2bec55edc31f63f2afdfba109ea |
| upstream: |
| hf_id: google/civil_comments |
| hf_config: default |
| license: cc0-1.0 |
| license_as_stated_by_source: cc0-1.0 |
| soft_labels: true |
| transformations: |
| - state and question are JSON text in the source and here; they are decoded and re-encoded compactly (orjson, |
| key order preserved), so the decoded values are identical to the source's and can be sent to POST /v1/systemone |
| as-is. |
| - 'options: choice = criteria keys in order; score = level indices ''0''..''K-1''; noul = [''0'', ''1''].' |
| - 'soft_label normalized to {option: probability}: noul scalar P(yes) p -> {''0'': 1 - p, ''1'': p}; score array |
| -> keyed by level index; choice object -> every option, absent options 0.0. Stored as JSON text; the text ''null'' |
| when the source has none.' |
| - id and label copied from the source; rows kept in source order; no rows added, dropped, or rewritten. |
| - upstream = the original dataset jev-bench built this config from (hf_id in jev-bench's manifest.json); license |
| = that dataset's license as jev-bench states it, without the parenthetical note. |
| - 'jev-bench build note: Natural class balance (~8% toxic); test cap raised to 2000 so positives are not too thin. |
| train/validation are drawn from the 97k-row HF validation split (the 1.8M-row train split is not needed).' |
| - config: measuring_hate_speech |
| suite: moderation |
| kinds: |
| - score |
| description: Does the comment contain hate speech? Three levels with annotator distributions as soft labels. |
| splits: |
| test: |
| file: moderation/measuring_hate_speech/test.jsonl |
| rows: 1000 |
| rows_with_soft_label: 1000 |
| sha256: 7bee80733dcec403f18fa21839b385ecdd4a4ca51498c9a7149b4ff6abd6d345 |
| validation: |
| file: moderation/measuring_hate_speech/validation.jsonl |
| rows: 500 |
| rows_with_soft_label: 500 |
| sha256: 21d04576fe51df0a4d326b47f66b50599d30a22a8791cd3e8b1f49a2bf1e15a7 |
| source: |
| hf_id: Praveenrajus/jev-bench |
| hf_config: measuring_hate_speech |
| revision: 18f88da81c28c2bec55edc31f63f2afdfba109ea |
| upstream: |
| hf_id: ucberkeley-dlab/measuring-hate-speech |
| hf_config: default |
| license: cc-by-4.0 |
| license_as_stated_by_source: cc-by-4.0 |
| soft_labels: true |
| transformations: |
| - state and question are JSON text in the source and here; they are decoded and re-encoded compactly (orjson, |
| key order preserved), so the decoded values are identical to the source's and can be sent to POST /v1/systemone |
| as-is. |
| - 'options: choice = criteria keys in order; score = level indices ''0''..''K-1''; noul = [''0'', ''1''].' |
| - 'soft_label normalized to {option: probability}: noul scalar P(yes) p -> {''0'': 1 - p, ''1'': p}; score array |
| -> keyed by level index; choice object -> every option, absent options 0.0. Stored as JSON text; the text ''null'' |
| when the source has none.' |
| - id and label copied from the source; rows kept in source order; no rows added, dropped, or rewritten. |
| - upstream = the original dataset jev-bench built this config from (hf_id in jev-bench's manifest.json); license |
| = that dataset's license as jev-bench states it, without the parenthetical note. |
| - 'jev-bench build note: Aggregated from annotator-level rows; soft_label = annotator vote shares over the 3 levels.' |
| - config: go_emotions |
| suite: moderation |
| kinds: |
| - choice |
| description: Which emotion does a Reddit comment primarily express (27 emotions + neutral)? soft_label = rater |
| vote shares. |
| splits: |
| test: |
| file: moderation/go_emotions/test.jsonl |
| rows: 1000 |
| rows_with_soft_label: 1000 |
| sha256: dfff5f21824fe2ef96b9a51db1d2635977ea9275638175001f2afcbf9b1abe58 |
| validation: |
| file: moderation/go_emotions/validation.jsonl |
| rows: 500 |
| rows_with_soft_label: 500 |
| sha256: 82a47b4d1401d181bc043736a6f043e79c611c3dc26d9a3929d53f3e69436620 |
| source: |
| hf_id: Praveenrajus/jev-bench |
| hf_config: go_emotions |
| revision: 18f88da81c28c2bec55edc31f63f2afdfba109ea |
| upstream: |
| hf_id: google-research-datasets/go_emotions |
| hf_config: raw |
| license: apache-2.0 |
| license_as_stated_by_source: apache-2.0 |
| soft_labels: true |
| transformations: |
| - state and question are JSON text in the source and here; they are decoded and re-encoded compactly (orjson, |
| key order preserved), so the decoded values are identical to the source's and can be sent to POST /v1/systemone |
| as-is. |
| - 'options: choice = criteria keys in order; score = level indices ''0''..''K-1''; noul = [''0'', ''1''].' |
| - 'soft_label normalized to {option: probability}: noul scalar P(yes) p -> {''0'': 1 - p, ''1'': p}; score array |
| -> keyed by level index; choice object -> every option, absent options 0.0. Stored as JSON text; the text ''null'' |
| when the source has none.' |
| - id and label copied from the source; rows kept in source order; no rows added, dropped, or rewritten. |
| - upstream = the original dataset jev-bench built this config from (hf_id in jev-bench's manifest.json); license |
| = that dataset's license as jev-bench states it, without the parenthetical note. |
| - 'jev-bench build note: v0.1.1: rebuilt from the raw config with rater vote shares as soft labels (v0.1 used |
| the single-label ''simplified'' subset).' |
| - config: helpsteer2_helpfulness |
| suite: quality |
| kinds: |
| - score |
| description: Rate how helpful an assistant response is to the user's prompt (HelpSteer2 helpfulness, 0–4). |
| splits: |
| test: |
| file: quality/helpsteer2_helpfulness/test.jsonl |
| rows: 1000 |
| rows_with_soft_label: 0 |
| sha256: 015fd63ff51182475b3224d49bd79aee5fa195684faa16bdab1cfe8dc2096dd7 |
| validation: |
| file: quality/helpsteer2_helpfulness/validation.jsonl |
| rows: 500 |
| rows_with_soft_label: 0 |
| sha256: b43d36c617b0d93e95014b6b132b6cb9a6a8bb149daed6ec21e01c226dd96ae8 |
| source: |
| hf_id: Praveenrajus/jev-bench |
| hf_config: helpsteer2_helpfulness |
| revision: 18f88da81c28c2bec55edc31f63f2afdfba109ea |
| upstream: |
| hf_id: nvidia/HelpSteer2 |
| hf_config: null |
| license: cc-by-4.0 |
| license_as_stated_by_source: cc-by-4.0 |
| soft_labels: false |
| transformations: |
| - state and question are JSON text in the source and here; they are decoded and re-encoded compactly (orjson, |
| key order preserved), so the decoded values are identical to the source's and can be sent to POST /v1/systemone |
| as-is. |
| - 'options: choice = criteria keys in order; score = level indices ''0''..''K-1''; noul = [''0'', ''1''].' |
| - 'soft_label normalized to {option: probability}: noul scalar P(yes) p -> {''0'': 1 - p, ''1'': p}; score array |
| -> keyed by level index; choice object -> every option, absent options 0.0. Stored as JSON text; the text ''null'' |
| when the source has none.' |
| - id and label copied from the source; rows kept in source order; no rows added, dropped, or rewritten. |
| - upstream = the original dataset jev-bench built this config from (hf_id in jev-bench's manifest.json); license |
| = that dataset's license as jev-bench states it, without the parenthetical note. |
| - config: stsb |
| suite: quality |
| kinds: |
| - score |
| description: Rate how similar in meaning two sentences are on the 0–5 STS scale. |
| splits: |
| test: |
| file: quality/stsb/test.jsonl |
| rows: 1000 |
| rows_with_soft_label: 0 |
| sha256: 5318b1f0f82f0ddd79a7911edc76201c313308181954ca957d7032bd60995365 |
| validation: |
| file: quality/stsb/validation.jsonl |
| rows: 500 |
| rows_with_soft_label: 0 |
| sha256: bb5eadd23567f143a516caf6ccdcbfd67415d69867b81f82d553d814cee8e0ae |
| source: |
| hf_id: Praveenrajus/jev-bench |
| hf_config: stsb |
| revision: 18f88da81c28c2bec55edc31f63f2afdfba109ea |
| upstream: |
| hf_id: sentence-transformers/stsb |
| hf_config: default |
| license: cc-by-sa-4.0 |
| license_as_stated_by_source: cc-by-sa-4.0 (STS Benchmark) |
| soft_labels: false |
| transformations: |
| - state and question are JSON text in the source and here; they are decoded and re-encoded compactly (orjson, |
| key order preserved), so the decoded values are identical to the source's and can be sent to POST /v1/systemone |
| as-is. |
| - 'options: choice = criteria keys in order; score = level indices ''0''..''K-1''; noul = [''0'', ''1''].' |
| - 'soft_label normalized to {option: probability}: noul scalar P(yes) p -> {''0'': 1 - p, ''1'': p}; score array |
| -> keyed by level index; choice object -> every option, absent options 0.0. Stored as JSON text; the text ''null'' |
| when the source has none.' |
| - id and label copied from the source; rows kept in source order; no rows added, dropped, or rewritten. |
| - upstream = the original dataset jev-bench built this config from (hf_id in jev-bench's manifest.json); license |
| = that dataset's license as jev-bench states it, without the parenthetical note. |
| - config: jev_decisions_v1 |
| suite: agent_action |
| kinds: |
| - choice |
| description: 'Next-action selection for tool-using agents: given the visible agent state, which of the available |
| tools/actions should be called next?' |
| splits: |
| test: |
| file: agent_action/jev_decisions_v1/test.jsonl |
| rows: 1000 |
| rows_with_soft_label: 0 |
| sha256: b8e6fab878da5aceef0dd00a5cbd91a202552fdb934881471cc4c371e24374b9 |
| source: |
| hf_id: samatv256/jev-decisions-v1 |
| hf_config: default |
| hf_split: test |
| file: data/test/test-00000-of-00001.parquet |
| revision: c12aadf1f01c72616bfab0b02480e21806397669 |
| upstream: |
| - hf_id: nvidia/Nemotron-SFT-Agentic-v2 |
| - hf_id: nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1 |
| - hf_id: nvidia/Nemotron-RL-Agentic-Function-Calling-Pivot-v1 |
| - hf_id: nvidia/Open-SWE-Traces |
| license: per row |
| licenses: |
| - Apache-2.0 |
| - BSD-2-Clause |
| - BSD-3-Clause |
| - MIT |
| - cc-by-4.0 |
| license_rule: Rows whose upstream is nvidia/Open-SWE-Traces carry the SPDX id of the source repository (provenance.source_metadata_json.repo_license) |
| in license; an Open-SWE-Traces row without a usable SPDX id would keep cc-by-4.0 and is counted in selection.license_fallbacks. |
| Rows from the Nemotron datasets carry no repository license and are cc-by-4.0. Every row is also subject to |
| the CC BY 4.0 attribution terms of jev-decisions-v1 and its NVIDIA upstream datasets. |
| license_as_stated_by_source: cc-by-4.0 (dataset card). All four NVIDIA upstream cards list CC BY 4.0; some also |
| list Apache-2.0/MIT (and BSD for Open-SWE-Traces). Open-SWE-Traces records carry a per-repository SPDX license |
| (provenance.source_metadata_json.repo_license). See the source's SOURCE_LICENSES.md before redistribution. |
| soft_labels: false |
| transformations: |
| - 'Source: the test partition only (data/test/test-00000-of-00001.parquet, one shard), read in Arrow batches from |
| the Hugging Face cache.' |
| - 'Eligibility: training.choice_eligible is true; 2..255 candidates; ordered_targets empty; candidate names non-empty |
| and unique; target.candidate_id matches exactly one candidate whose name equals target.action_name.' |
| - 'Token cap: rows whose state+question exceed ~32000 tokens (serialized JSON chars / 3, the validator''s warning |
| threshold) are excluded before sampling; no row is truncated.' |
| - 'question.type = ''choice''; question.instructions = the fixed Choice question the publisher uses in its general-clean-50k |
| config: ''Given the current state and available options,\nwhich option should be selected?''. The record carries |
| no per-row question text; the user''s task stays in state.user_goal.' |
| - 'question.criteria = {candidate.name: candidate.description, or null when empty}, in source candidate order. |
| Parameter schemas, candidate metadata, and target arguments are not included.' |
| - label = target.action_name (the matched candidate's name); options = criteria keys in order; soft_label = null. |
| - 'state = {system, user_goal, environment, history}: system and user_goal copied as strings (omitted when null/empty; |
| kept even when they repeat a history turn); environment = decoded state.environment_json (omitted when null/empty); |
| history = [{role, content}] with content = decoded payload_json. Serialized JSON that does not parse is kept |
| as the raw string (count below).' |
| - upstream = the record's source field (the NVIDIA dataset it was derived from); license = see license_rule. |
| - id = 'jev_decisions_v1/test/<source id>'. Labels, provenance, and training fields are never copied into state. |
| - 'Sampling: candidate-count buckets 2, 3-4, 5-8, 9-16, 17+; the 1,000 rows are split across buckets in proportion |
| to rows available after the token cap (largest-remainder method); within a bucket, rows with the smallest sha256(''20260930:<source |
| id>'') are taken. Selection is independent of source row order. Rows are written by bucket, then by that key.' |
| selection: |
| seed: 20260930 |
| size: 1000 |
| source_rows: 354635 |
| excluded: |
| candidate_count_outside_2_255: 8515 |
| not_choice_eligible: 174934 |
| over_token_limit: 70137 |
| buckets: |
| - bucket: '2' |
| eligible: 5903 |
| within_token_cap: 5853 |
| selected: 58 |
| - bucket: 3-4 |
| eligible: 112955 |
| within_token_cap: 43053 |
| selected: 426 |
| - bucket: 5-8 |
| eligible: 13925 |
| within_token_cap: 13867 |
| selected: 137 |
| - bucket: 9-16 |
| eligible: 21405 |
| within_token_cap: 21335 |
| selected: 211 |
| - bucket: 17+ |
| eligible: 16998 |
| within_token_cap: 16941 |
| selected: 168 |
| by_upstream: |
| - hf_id: nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1 |
| eligible: 1972 |
| within_token_cap: 1972 |
| selected: 17 |
| - hf_id: nvidia/Nemotron-RL-Agentic-Function-Calling-Pivot-v1 |
| eligible: 108 |
| within_token_cap: 108 |
| selected: 1 |
| - hf_id: nvidia/Nemotron-SFT-Agentic-v2 |
| eligible: 68297 |
| within_token_cap: 68009 |
| selected: 668 |
| - hf_id: nvidia/Open-SWE-Traces |
| eligible: 100809 |
| within_token_cap: 30960 |
| selected: 314 |
| by_license: |
| - license: cc-by-4.0 |
| selected: 686 |
| - license: MIT |
| selected: 183 |
| - license: Apache-2.0 |
| selected: 100 |
| - license: BSD-3-Clause |
| selected: 25 |
| - license: BSD-2-Clause |
| selected: 6 |
| by_upstream_and_license: |
| - hf_id: nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1 |
| license: cc-by-4.0 |
| selected: 17 |
| - hf_id: nvidia/Nemotron-RL-Agentic-Function-Calling-Pivot-v1 |
| license: cc-by-4.0 |
| selected: 1 |
| - hf_id: nvidia/Nemotron-SFT-Agentic-v2 |
| license: cc-by-4.0 |
| selected: 668 |
| - hf_id: nvidia/Open-SWE-Traces |
| license: Apache-2.0 |
| selected: 100 |
| - hf_id: nvidia/Open-SWE-Traces |
| license: BSD-2-Clause |
| selected: 6 |
| - hf_id: nvidia/Open-SWE-Traces |
| license: BSD-3-Clause |
| selected: 25 |
| - hf_id: nvidia/Open-SWE-Traces |
| license: MIT |
| selected: 183 |
| license_fallbacks: 0 |
| selected_trajectories: 945 |
| max_rows_per_trajectory: 4 |
| json_decode_fallbacks: 0 |
|
|
