| --- |
| license: apache-2.0 |
| task_categories: |
| - text-classification |
| language: |
| - en |
| pretty_name: Agent Task Classifier Dataset (laya loop-taxonomy v2) |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - agent |
| - routing |
| - task-classification |
| - decision-model |
| - laya |
| --- |
| |
| # agent-task-classifier-dataset |
|
|
| 5,154 labeled English training examples (plus 54 held-out) for classifiers that map a user |
| request (to a personal-assistant agent) to the **agent-loop shape** it demands — the skeleton of |
| the high-level process a task of that kind must follow — rather than its topic. |
|
|
| Companion model: [kumarabd1996/agent-task-classifier](https://huggingface.co/kumarabd1996/agent-task-classifier) |
| (a fine-tuned [laya](https://huggingface.co/convaiinnovations/laya) checkpoint; 47/54 on the |
| held-out set here, vs 13/54 for the untuned base). |
|
|
| **v2** relabels the v1 corpus onto a nine-label set and adds ~1,500 personal-records and finance |
| scenarios (goals, routines, budgets, trackers and the lookups around them). The v1 files are in this |
| repo's git history. |
|
|
| ## The nine labels |
|
|
| | label | the loop it demands | |
| |---|---| |
| | `conversation` | questions, quick asks, lookups, a reported measurement, a single reminder, chatter — the default, safe fallback | |
| | `companion` | inner-life support with no outcome in the world (reflection, therapy) | |
| | `learn` | build the user's own ability over sessions (practice, tutoring) | |
| | `diagnose` | find the cause of a specific malfunction or anomaly, including in the user's own data | |
| | `research` | assemble understanding from investigation (multi-source, comparison, synthesis) | |
| | `produce` | make an artifact judged against a standard (document, spreadsheet, script, letter) | |
| | `transact` | a commitment or possession in the world: book, buy, pay, transfer, or complete a procedure | |
| | `stabilize` | urgent or deteriorating situation — act before full understanding | |
| | `plan` | set up or change the person's own standing structure: a goal, routine, budget/limit, or tracker | |
|
|
| v1 → v2: `make`→`produce`; `react`→`stabilize`; `arrange`/`acquire`/`execute`→`transact`; |
| `tend`→`conversation`; `plan` is new. Two requests share a label iff they demand the same loop |
| skeleton. Topic is irrelevant. |
|
|
| ## Format |
|
|
| `train.jsonl` — one JSON object per line, laya's native training format: |
|
|
| ```json |
| {"state": "<the request text>", "questions": {"loop": {"type": "choice", "instructions": "...", "criteria": {...}}}, "expected": {"loop": "<label>"}, "src": "<source>", "id": "<id>"} |
| ``` |
|
|
| Continuations carry the request being continued, in the exact format used at inference: |
|
|
| ``` |
| Earlier request: <prior request> |
| New request: <follow-up> |
| ``` |
|
|
| `eval.jsonl` — 54 held-out items: the 24 taxonomy boundary drills (relabelled) plus 30 hand-written |
| personal-records and finance cases (`eval_life_finance.json`, phrased differently from any template). |
| Never trained on. |
|
|
| ## Composition |
|
|
| | source (`src`) | what | license | |
| |---|---|---| |
| | `multiwoz`, `multiwoz-cont` | MultiWOZ 2.1 booking utterances + continuations (`transact`) | permissive (research; Budzianowski et al. 2018) | |
| | `massive` | MASSIVE en-US takeaway orders, transport bookings, sampled commands | CC-BY-4.0 (Amazon Science) | |
| | `oasst`, `oasst-cont` | OASST2 English prompts + continuations, model-labeled with the taxonomy spec, spot-audited | Apache-2.0 (OpenAssistant) | |
| | `synth`, `synth-cont`, `hard` | template × slot generation across the personal-assistant domains; labels by construction; hand-written boundary cases | Apache-2.0 (this release) | |
| | `lf`, `lf-cont`, `lf-hard` | personal-records and finance scenarios incl. short follow-ups ("All", "yes"); labels by construction | Apache-2.0 (this release) | |
|
|
| Label distribution (after per-class caps): conversation 1,300 · transact 1,200 · plan 633 · produce 600 · diagnose 551 · research 333 · learn 226 · companion 187 · stabilize 124. |
|
|
| ## Provenance and licensing |
|
|
| - **MASSIVE**: Amazon Science, CC-BY-4.0 — attribution required and given. |
| - **OASST2**: OpenAssistant Conversations Dataset, Apache-2.0. |
| - **MultiWOZ 2.1**: Budzianowski et al., 2018; distributed for research use. |
| - **Synthetic items**: generated for this release; scripts included (`generate_synthetic.py`, |
| `generate_life_finance.py`, `merge_v2.py`, `taxonomy_labels.py`) so the construction is auditable. |
| `generate_synthetic.py` still emits the v1 label names; `merge_v2.py` maps them to v2 (its inputs, the |
| v1 corpus files, are in this repo's git history, not in the current tree). |
|
|
| ## Limitations |
|
|
| - A large share is synthetic; template patterns bias the text distribution. The `plan` examples in |
| particular are template-built, so implicit phrasings ("I keep meaning to exercise more…") are |
| underrepresented. |
| - English only; nine fixed labels; out-of-taxonomy requests resolve to `conversation`. |
| - OASST2 labels are teacher-model labels (spot-audited), not fully human-verified. The MultiWOZ |
| "find a hotel" requests are labeled `transact`, a judgment call. |
| - 54 held-out items is a small evaluation set. |
| - **Privacy**: public datasets and synthetic text only. The maintainer's own data is excluded. |
|
|
