| | --- |
| | dataset_info: |
| | features: |
| | - name: text |
| | dtype: string |
| | - name: category |
| | dtype: string |
| | - name: extended_answer |
| | sequence: |
| | - name: user |
| | dtype: string |
| | - name: answer |
| | dtype: string |
| | splits: |
| | - name: train |
| | num_bytes: 363151819 |
| | num_examples: 54348 |
| | download_size: 136276329 |
| | dataset_size: 363151819 |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: data/train-* |
| | --- |
| | # DATASET: **Kazakh administrative documents for RAG document QA.** |
| |
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| | * **Structure.** Each item is a JSON object with: |
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| | * `text`: the full Kazakh document body (biography or power-of-attorney). |
| | * `category`: document type label — e.g., **Өмірбаян** (autobiographical CV/biography) and **Сенімхат** (power of attorney) etc. In Kazakh admin usage, *Өмірбаян* is a concise, chronological personal record; *Сенімхат* is a written authorization to act on someone’s behalf. |
| | * `extended_answer`: list of `{user, answer}` QA pairs extractable from `text` (factoid fields like birth date/place, degrees, awards; or principals/children, validity period, addresses, etc.). |
| |
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| | * **Scope.** Kazakh-language **administrative and personal records** with explicit slot-like facts (names, dates, institutions, addresses, phone numbers) and templated legal phrasing (e.g., “сенімхат … жарамды”, placeholders like `[күні]`). The two shown categories align with common Kazakh document genres: autobiographies for employment/education workflows and powers of attorney for representation/transport of minors. |
| |
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| | * **Usage.** |
| |
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| | * **Extraction & slot filling:** train/evaluate NER/IE for structured fields (person, DOB, place, degree, positions; principal/agent, children, validity window). |
| | * **Document QA / RAG:** `extended_answer` provides supervision for extractive/generative QA grounded in `text`. |
| | * **Template validation & completion:** detect missing placeholders (e.g., `[күні]`) and verify mandatory fields typical for *сенімхат*; learn document-type–specific consistency rules. |
| | * **Document classification:** use `category` to train classifiers distinguishing biography vs. authorization letters. |
| | * **Privacy stress-tests:** includes realistic PII (addresses, phone numbers) to test redaction or safe-answering policies (if needed). |
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| | **Notes.** No cross-file alignment is required; each JSON is self-contained: raw text + gold QA pairs enable end-to-end pipelines (parse → retrieve within doc → answer). The dataset is suitable for low-resource Kazakh NLP where domain conventions for *өмірбаян* and *сенімхат* are well-defined. |
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