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+---
+license: apache-2.0
+language:
+- en
+pretty_name: LifeTextMultiTurnStreamingCoT
+tags:
+- streaming-cot
+- life-scenarios
+- text
+- multi-turn
+- dialogue
+- sft
+- reasoning
+- instruction-tuning
+task_categories:
+- text-generation
+- question-answering
+task_ids:
+- language-modeling
+size_categories: 1K<n<10K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train.parquet
+  - split: eval
+    path: data/eval.parquet
+- config_name: high_quality
+  data_files:
+  - split: train
+    path: data/high_quality_train.parquet
+  - split: eval
+    path: data/high_quality_eval.parquet
+---
+
+# LifeTextMultiTurnStreamingCoT v0.4
+
+**Final professional public release** — clean SFT schema, target field, canonical taxonomy.
+
+## Overview
+
+- **Modality**: Text
+- **Turn Type**: Multi Turn
+- **Version**: v0.4
+- **License**: apache-2.0
+- **Language**: English
+- **HF Repo**: `skyzhou06/LifeTextMultiTurnStreamingCoT`
+
+## Row Counts
+
+| Split | Rows |
+|-------|------|
+| Train | 7,955 |
+| Eval  | 2,045 |
+| High Quality Train | 4,690 |
+| High Quality Eval  | 1,233 |
+| **Total** | **10,000** |
+
+## Schema (v0.4)
+
+### Top-Level Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | string | Stable example ID |
+| `split` | string | `train` or `eval` |
+| `modality` | string | `text` |
+| `turn_type` | string | `multi_turn` |
+| `input` | object | Input data |
+| `streaming` | object | Checkpoints with natural-language reasoning |
+| `target` | object | Training target: reasoning, answer, response |
+| `taxonomy` | object | Canonical content classification |
+| `quality` | object | Quality assessment |
+| `source` | object | Provenance |
+| `metadata` | object | Release metadata |
+
+### `target`
+
+```json
+{
+  "reasoning": "Natural-language reasoning summary.",
+  "answer": "The final answer.",
+  "response": "Reasoning: ...\n\nAnswer: ..."
+}
+```
+
+- `target.answer` — for answer-only SFT
+- `target.response` — for reasoning-augmented SFT
+
+### `taxonomy`
+
+Uses canonical enum categories: `daily_life`, `travel`, `education`, `work_productivity`, `finance_consumer`, `health_wellness_safe`, `tech_support`, `information_extraction`, `creative_planning`, `social_communication`.
+
+### `quality`
+
+```json
+{
+  "is_high_quality": true,
+  "sft_ready": true,
+  "natural_reasoning": true,
+  "reasoning_quality": "high",
+  "taxonomy_quality": "high"
+}
+```
+
+## Changes from v0.3
+
+- `output` renamed to `target` with `reasoning`, `answer`, `response`
+- `streaming.trace` removed from active rows
+- `metadata.legacy` blobs removed
+- Taxonomy mapped to canonical enum with fixed category/subcategory pairs
+- `high_quality` split into `high_quality_train` / `high_quality_eval`
+- `metadata.release_version` = `"v0.4"`
+
+## SFT Usage
+
+```python
+from datasets import load_dataset
+
+# Default config
+ds = load_dataset("skyzhou06/LifeTextMultiTurnStreamingCoT")
+# ds["train"]["target"]["response"]  — reasoning + answer
+# ds["train"]["target"]["answer"]    — answer only
+
+# High quality config
+ds_hq = load_dataset("skyzhou06/LifeTextMultiTurnStreamingCoT", "high_quality")
+```
+
+## Source Licenses
+
+Dataset-level license: **apache-2.0**. Individual rows include `source.license` and `source.dataset` fields with source-specific license information.
+
+## Limitations
+
+- Reasoning is rule-based (content-grounded)
+- Some answers are brief closing phrases (check `quality.sft_ready`)
+- Non-English examples not included
+
+## Citation
+
+If you use this dataset, please cite the original source datasets and this release.