| --- |
| pretty_name: tasksource-jev-typed-decisions |
| language: |
| - en |
| - multilingual |
| license: other |
| task_categories: |
| - zero-shot-classification |
| - text-classification |
| - question-answering |
| - token-classification |
| tags: |
| - tasksource |
| - jev |
| - system-one |
| - runtime-defined-decisions |
| - decision-models |
| - multiple-choice |
| - decision-model |
| size_categories: |
| - 1M<n<10M |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test |
| path: data/test-* |
| - config_name: filtered-full |
| data_files: |
| - split: train |
| path: filtered-full/train-*.parquet |
| - config_name: full |
| data_files: |
| - split: train |
| path: full/train-* |
| - split: validation |
| path: full/validation-* |
| - split: test |
| path: full/test-* |
| - config_name: vision |
| data_files: |
| - split: train |
| path: vision/train-* |
| - split: test |
| path: vision/test-* |
| - split: validation |
| path: vision/validation-* |
| dataset_info: |
| - config_name: default |
| features: |
| - name: state |
| dtype: string |
| - name: kind |
| dtype: string |
| - name: id |
| dtype: string |
| - name: options |
| list: string |
| - name: target |
| list: float64 |
| - name: question |
| dtype: string |
| - name: source |
| dtype: string |
| - name: variant |
| dtype: string |
| - name: split |
| dtype: string |
| - name: source_index |
| dtype: string |
| - name: group_id |
| dtype: string |
| - name: question_id |
| dtype: string |
| - name: example_id |
| dtype: string |
| - name: license |
| dtype: string |
| - name: license_use |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1487877581 |
| num_examples: 999846 |
| - name: validation |
| num_bytes: 21838060 |
| num_examples: 15000 |
| - name: test |
| num_bytes: 20936329 |
| num_examples: 15000 |
| download_size: 690439654 |
| dataset_size: 1530651970 |
| - config_name: filtered-full |
| features: |
| - name: state |
| dtype: string |
| - name: kind |
| dtype: string |
| - name: id |
| dtype: string |
| - name: options |
| list: string |
| - name: target |
| list: float64 |
| - name: question |
| dtype: string |
| - name: source |
| dtype: string |
| - name: variant |
| dtype: string |
| - name: split |
| dtype: string |
| - name: group_id |
| dtype: string |
| - name: question_id |
| dtype: string |
| - name: license |
| dtype: string |
| - name: license_use |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 1633306939 |
| num_examples: 1305478 |
| download_size: 335270018 |
| dataset_size: 1633306939 |
| - config_name: full |
| features: |
| - name: state |
| dtype: string |
| - name: kind |
| dtype: string |
| - name: id |
| dtype: string |
| - name: options |
| list: string |
| - name: target |
| list: float64 |
| - name: question |
| dtype: string |
| - name: source |
| dtype: string |
| - name: variant |
| dtype: string |
| - name: split |
| dtype: string |
| - name: source_index |
| dtype: string |
| - name: group_id |
| dtype: string |
| - name: question_id |
| dtype: string |
| - name: example_id |
| dtype: string |
| - name: license |
| dtype: string |
| - name: license_use |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 3720266876 |
| num_examples: 2500000 |
| - name: validation |
| num_bytes: 21838060 |
| num_examples: 15000 |
| - name: test |
| num_bytes: 20936329 |
| num_examples: 15000 |
| download_size: 1867584732 |
| dataset_size: 3763041265 |
| - config_name: vision |
| features: |
| - name: images |
| list: image |
| - name: metadata |
| dtype: string |
| - name: id |
| dtype: string |
| - name: kind |
| dtype: string |
| - name: options |
| list: string |
| - name: target |
| list: float64 |
| - name: state |
| dtype: string |
| - name: question |
| dtype: string |
| - name: source |
| dtype: string |
| - name: variant |
| dtype: string |
| - name: split |
| dtype: string |
| - name: group_id |
| dtype: string |
| - name: question_id |
| dtype: string |
| - name: example_id |
| dtype: string |
| - name: license |
| dtype: string |
| - name: license_use |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 181690421524 |
| num_examples: 479826 |
| - name: test |
| num_bytes: 146575133 |
| num_examples: 475 |
| - name: validation |
| num_bytes: 274444703 |
| num_examples: 972 |
| download_size: 108822013028 |
| dataset_size: 182111441360 |
| --- |
| |
| # tasksource-jev-typed-decisions |
|
|
| Typed decisions from hundreds of curated [Tasksource](https://github.com/sileod/tasksource) tasks: classification, multiple choice, ordered ratings, probabilities and visual reasoning. Targets come from source annotations or deterministic transformations of them. Native annotation noise and subjective judgments remain. |
|
|
| ## Load |
|
|
| ```python |
| from datasets import load_dataset |
| |
| text = load_dataset("tasksource/tasksource-jev-typed-decisions") |
| vision = load_dataset("tasksource/tasksource-jev-typed-decisions", "vision") |
| row = text["train"][0] |
| print(row["state"], row["question"], row["options"], row["target"]) |
| ``` |
|
|
| | Config | Contents | |
| |---|---| |
| | `default` | Steered text training mix, plus reviewed incremental additions; validation and test included. | |
| | `full` | Larger text pool with per-source caps, including incremental additions; validation and test included. | |
| | `filtered-full` | Filtered, training-only historical snapshot. Later additions are not included. See [selection policy and counts](filtered-full/README.md). | |
| | `vision` | Multimodal decisions with ordered images and text choices. See [visual sources, sampling and provenance](vision/README.md). | |
|
|
| Exact split sizes are in the Dataset Viewer metadata. Task coverage and counts are in [sources.yaml](sources.yaml) and [vision/sources.yaml](vision/sources.yaml). |
|
|
| ## Row format |
|
|
| | Field | Meaning | |
| |---|---| |
| | `state` | Text to reason about. | |
| | `question` | The decision to make. | |
| | `kind` | `choice`, `score` or `noul`. | |
| | `options` | Criteria in their presented order; empty for `noul`. | |
| | `target` | Distribution aligned with `options`, or `[p_true]` for `noul`. | |
| | `id`, `group_id`, `question_id` | Decision identity and grouping of related questions. | |
| | `example_id` | Content-derived example identity used by the build. | |
| | `source_index` | Original row of the example in its source dataset, as `split:row` (the split before any re-splitting); empty for packed and generated rows. | |
| | `source`, `split`, `variant` | Task identity, split annotation and recast variant. | |
| | `license`, `license_use` | Recorded source terms and their usage classification. | |
| | `images` | **Vision only:** ordered Hugging Face image features, decoded on access. | |
| | `metadata` | **Vision only:** JSON-string source identity, geometry, augmentation and license evidence. | |
|
|
| ```json |
| {"state": "My body cast a shadow over the grass. What was the cause of this?", |
| "question": "Choose the criterion that best answers the question.", |
| "kind": "choice", "options": ["The sun was rising.", "The grass was cut."], |
| "target": [1.0, 0.0], "source": "super_glue/copa"} |
| ``` |
|
|
| `choice` selects a criterion; `score` uses an ordered scale. Soft targets preserve annotator disagreement or interpolate numerical ratings between neighboring scale anchors. `noul` represents the probability that a proposition is true. Scale meaning is determined by the question and criteria. |
|
|
| Rows sharing `group_id` can be assembled into a multi-question request. Vision images stay separate from text and must be passed through the model's image adapter; answer options remain text. See [AGENTS.md](AGENTS.md) for request assembly and row semantics. |
|
|
| ## Construction and evaluation |
|
|
| Tasksource standardizes native labels and choices, adds task-specific questions where needed, and applies deterministic option permutations and low-frequency text variants. Some text rows pack related decisions over a shared state. A decision's majority label keeps at most three rows per row of its other labels (graded answers count as yes above 0.5; a question with a single label is dropped), so skewed binary sources such as answer selection or toxicity no longer reward always answering the common label; procedural questions keep each label under 60%. The visual config contains direct decisions and shares sampling budgets across related task views. |
|
|
| Native source partitions are retained where available; derived group-based holdouts and overlap exclusions are documented per source. These checks do not establish absence of all cross-dataset or benchmark contamination. For example, Mind2Web text tasks use derived holdouts from public training trajectories, not official benchmark tests; alignment with private Decision Index evaluation rows is unverified. Mind2Web is excluded from the visual config. |
|
|
| Source and recast reviews are coarse checks, not corpus-wide correctness guarantees. [English examples](https://github.com/sileod/tasksource/blob/main/docs/examples.md) illustrate the exported and canonical representations. |
|
|
| ## Licenses |
|
|
| This collection has **mixed source terms**, hence `license: other`. Original annotation and image terms still apply. `license_use` is a best-effort classification: `commercial`, `non-commercial` or `unspecified`; it is not legal clearance. Missing or scoped evidence is retained explicitly. |
|
|
| ```python |
| text = text.filter(lambda use: use == "commercial", input_columns="license_use") |
| ``` |
|
|
| Visual annotation licenses may not cover third-party images. The visual license review records unresolved image rights and explicit restrictions, including FigureQA's prohibition on redistribution. See [component-level evidence](vision/license-review.json) and the [vision documentation](vision/README.md) before reuse. |
|
|
| ## Documentation and provenance |
|
|
| - [Text sources and revisions](sources.yaml), [release audit](release-audit.json), [build manifest](build-manifest.json) and [failed sources](failed-tasks.json). |
| - [Vision documentation](vision/README.md) and [filtered-full selection evidence](quality/filtered-full-v1/README.md). |
| - [Build runbook](https://github.com/sileod/tasksource/blob/main/docs/jev/README.md), [base build recipe](BUILD.md) and [task catalogs](https://github.com/sileod/tasksource#task-catalogs). |
| - [Release history](CHANGELOG.md). Addition manifests and sampled reviews retain their original snapshot context. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{sileo-2024-tasksource, |
| title = {tasksource: A Large Collection of {NLP} tasks with a Structured Dataset Preprocessing Framework}, |
| author = {Sileo, Damien}, |
| booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)}, |
| year = {2024}, |
| pages = {15655--15684}, |
| url = {https://aclanthology.org/2024.lrec-main.1361/} |
| } |
| ``` |
|
|
