| --- |
| license: cc-by-4.0 |
| pretty_name: TurnFlow |
| language: |
| - en |
| - zh |
| task_categories: |
| - text-generation |
| tags: |
| - benchmark |
| - evaluation |
| - multi-turn |
| - user-simulation |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: scenarios |
| default: true |
| data_files: |
| - split: test |
| path: scenarios/*.jsonl |
| - config_name: judges |
| data_files: |
| - split: test |
| path: judges/*.jsonl |
| --- |
| |
| # TurnFlow |
|
|
| A versioned collection of **490 synthetic multi-turn scenarios** and their |
| source-bound judging contracts. The corresponding simulator, runner, compiler, |
| and scoring rules are available at [X-EASys/TurnFlow](https://github.com/X-EASys/TurnFlow). |
| Version **0.4.0** uses contiguous task IDs **T1–T5**, based on the rc5 source snapshot. |
| This version changes task/source identifiers and derived hashes; scenario content |
| and scoring rules are unchanged. Earlier tags retain their original identifiers. |
|
|
| | Task | Description | Sources | |
| |---|---|---:| |
| | T1 | Stateful Multi-Constraint Following | 100 | |
| | T2 | Scope Creep | 79 | |
| | T3 | Constraint Collision | 100 | |
| | T4 | Preference Override | 97 | |
| | T5 | Goal Shift | 114 | |
|
|
| ## Load the data |
|
|
| ```python |
| import json |
| from datasets import load_dataset |
| |
| sources = load_dataset("Buka7yo/TurnFlow", "scenarios", revision="v0.4.0", split="test") |
| judges = load_dataset("Buka7yo/TurnFlow", "judges", revision="v0.4.0", split="test") |
| scenario = json.loads(sources[0]["scenario_json"]) |
| contract = json.loads(judges[0]["definition_json"]) |
| ``` |
|
|
| Both configurations contain the same 490 source keys in a single `test` split. |
| There is no training or validation split. T1–T5 identify the five released tasks; |
| the full `source_key` distinguishes variants sharing a bare ID. |
|
|
| ### Scenario rows |
|
|
| - `source_key`: complete source identity, for example `T4/v3/T4_400`. |
| - `task`: T1, T2, T3, T4, or T5. |
| - `domain`: the source's scenario domain. |
| - `source_sha256`: SHA256 of the UTF-8 bytes in `scenario_json`. |
| - `scenario_json`: the exact source JSON text, preserving the packaged source bytes. |
|
|
| The parsed scenario contains the initial situation, private state/aim sequence, |
| constraints, and ground-truth information. The evaluated assistant must receive |
| only the conversation and public base instruction, without this private state or |
| the judge definition. The released runner enforces this separation. |
|
|
| ### Judge rows |
|
|
| - `source_key`, `task`, `source_sha256`: join keys back to the scenario. |
| - `profile`: source-specific parser/representation profile. |
| - `definition_json`: the frozen judge definition; T2/T4 include the source-bound |
| template and structured specification, while T1/T3/T5 use their fact definitions. |
| - `definition_sha256`: SHA256 of the UTF-8 `definition_json` string. |
| - `catalog_json`: source-binding and definition metadata used by the matching runtime. |
|
|
| These contracts depend on the matching compiler and parser. They are not a list |
| of scalar labels for completed assistant responses. Generic judge prompting or |
| changing aggregation thresholds defines a different evaluation protocol. |
|
|
| ## Additional files |
|
|
| `protocol.json` specifies the simulator/judge defaults and source ordering. |
| `bindings.json` selects source-bound simulator rendering. `runtime_resources/` |
| contains the JSON resources used by the code's prompt compiler and reducer. |
| `manifest.json` records per-source, per-definition, and file hashes, plus the |
| matching code fingerprint and dataset-manifest hash. |
|
|
| For reproduction, pin the GitHub tag **v0.4.0** and this repository's **v0.4.0** |
| tag. The GitHub `release.json` also pins the exact Hugging Face commit. Installation |
| of the Python package includes all sources and needs no Hugging Face account. |
|
|
| ## Intended use and limitations |
|
|
| This dataset supports evaluating assistants' behavior across evolving goals, |
| constraints, scope changes, and preferences in multi-turn conversations. The |
| scenarios are constructed evaluation material, rather than real users' chat logs. |
| All sources and judging contracts are disclosed for reproducibility; there is no |
| claim that they are unseen by model training. |
|
|
| The default protocol uses Gemini 3.7 Flash for simulation and DeepSeek V4 Flash |
| with high reasoning for a single judge call per completed dialogue. Fact extraction |
| is probabilistic even though aggregation is deterministic. Source ambiguities, |
| interpretation boundaries, provider failures and model changes can affect scores. |
| This release does not establish universal judge correctness or invariant model |
| rankings. Report all model settings, dataset/code revisions, planned denominators, |
| coverage, and separate PASS/FAIL/U/NA/INVALID counts. |
|
|
| The repository contains benchmark inputs and contracts. Generated dialogues, |
| model performance tables, experiment logs, billing records, and internal analysis |
| reports are not distributed with it. The software and task documentation are at |
| [GitHub](https://github.com/X-EASys/TurnFlow). |
|
|
| ## License |
|
|
| The dataset materials are licensed under [CC BY 4.0](LICENSE). The matching |
| Python software is licensed separately under MIT. Please credit TurnFlow and |
| its contributors, link to the license, and indicate changes when sharing adapted |
| materials. |
|
|
