| ---
|
| license: apache-2.0
|
| task_categories:
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| - text-generation
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| language:
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| - en
|
| tags:
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| - intent-parsing
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| - structured-output
|
| - synthetic
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| - weather
|
| size_categories:
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| - 1K<n<10K
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| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: train.jsonl
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| - split: eval
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| path: eval.jsonl
|
| ---
|
| # weather-intent
|
|
|
| Synthetic dataset for fine-tuning a small model to parse a natural-language weather
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| question into a compact structured **intent** (JSON), scored by field-level exact
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| match. Trains [Nicholas55555/qwen2.5-1.5b-weather-intent](https://huggingface.co/Nicholas55555/qwen2.5-1.5b-weather-intent).
|
|
|
| ```json
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| {"utterance": "will it rain in Paris this weekend?",
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| "intent": {"location": "Paris", "date": "this_weekend", "metric": "rain", "time_of_day": null},
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| "category": "basic"}
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| ```
|
|
|
| ## Fields
|
|
|
| | field | description |
|
| |---|---|
|
| | `utterance` | the natural-language weather question |
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| | `intent` | target slots: `location`, `date`, `metric`, `time_of_day` |
|
| | `category` | failure-mode bucket (below) |
|
|
|
| ## Slot vocabulary
|
|
|
| | slot | values |
|
| |---|---|
|
| | `location` | place name, or `null` |
|
| | `date` | `today`, `tomorrow`, `day_after_tomorrow`, `this_weekend`, `next_weekend`, `next_week`, a weekday, or `null` |
|
| | `metric` | `temperature`, `rain`, `snow`, `wind`, `humidity`, `uv`, `cloud`, `general` |
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| | `time_of_day` | `morning`, `afternoon`, `evening`, `night`, or `null` |
|
|
|
| ## Splits
|
|
|
| | split | rows |
|
| |---|---|
|
| | train | 1200 |
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| | eval | 217 |
|
|
|
| The `eval` split is category-balanced with a hand-authored hard set. `category`
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| buckets each example by failure mode: `basic`, `multi_slot`, `implicit_slot`, `date_reasoning`, `vague`, `ood`.
|
|
|
| ## Generation
|
|
|
| Programmatic and correct-by-construction: slots are sampled first, the utterance is
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| rendered from them, so labels are exact. Deliberate phrasing variety (prefixes, slot
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| ordering, synonymous stems); an optional distillation mode paraphrases seeds with a
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| frontier model. The task is **parsing only** — volatile forecast facts and any
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| rendering live in downstream code, never in the labels.
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|
|
