| # Dataset Preparation and Representation Scripts |
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| This folder contains the official, verified dataset preparation, validation, and representation-building scripts for: |
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| > **"Beyond Chunking: Node Integrity and Field Structure in Bengali Retrieval-Augmented Agent Memory"** |
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| --- |
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| ## 1. Directory Structure |
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| ```text |
| reproducibility/scripts/ |
| ├── README.md # This guide |
| ├── data_ingestion/ |
| │ ├── 00_fetch_external_data.py # Validates external provenance and local file presence |
| │ ├── 01_prepare_corpora.py # Standardizes knowledge corpora across Agri, Legal, and Edu |
| │ └── 02_prepare_queries.py # Standardizes benchmark queries and evaluation subsets |
| ├── validation/ |
| │ └── 03_validate_data.py # Independent reproducibility audit gate |
| ├── representations/ |
| │ ├── 04_build_l1_chunks.py # L1 Chunked Unstructured builder (500-char window) |
| │ ├── 05_build_l2_full_nodes.py # L2 Full-Node Unstructured builder (intact concatenated text) |
| │ └── 06_build_l3_fields.py # L3 Structured BM25F schema builder (dedicated search slots) |
| ├── 00_fetch_external_data.py # Top-level entry point runner |
| ├── 01_prepare_corpora.py # Top-level entry point runner |
| ├── 02_prepare_queries.py # Top-level entry point runner |
| ├── 03_validate_data.py # Top-level entry point runner |
| ├── 04_build_l1_chunks.py # Top-level entry point runner |
| ├── 05_build_l2_full_nodes.py # Top-level entry point runner |
| └── 06_build_l3_fields.py # Top-level entry point runner |
| ``` |
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| --- |
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| ## 2. Script Execution Guide |
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| ### Script 00: Check External Data Sources and Provenance |
| Validates external data repositories (HuggingFace datasets, NCTB curriculum textbooks, AIS/DAE handbooks): |
| ```bash |
| python reproducibility/scripts/00_fetch_external_data.py |
| ``` |
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| ### Script 01: Ingest and Standardize Corpora |
| Standardizes raw nodes into canonical JSON schema (`structured_nodes.json`) and exports `selected_act_ids.json` (735 legal acts) and `nctb_provenance.json` (190 secondary experiments): |
| ```bash |
| python reproducibility/scripts/01_prepare_corpora.py |
| ``` |
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| ### Script 02: Prepare Benchmark Queries and Evaluation Subsets |
| Standardizes 3,670 queries (`queries.jsonl`) and generates the 900-query agent sample, the 872-query common evaluated subset, the 28 timeout exclusions, and the 300-query perturbation sample: |
| ```bash |
| python reproducibility/scripts/02_prepare_queries.py |
| ``` |
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| ### Script 03: Execute Independent Data Validation Audit Gate |
| Executes the cryptographic and census audit verifying 100% hash integrity against `manifest.json`, node counts, query counts, chunk counts, and referential integrity: |
| ```bash |
| python reproducibility/scripts/03_validate_data.py |
| ``` |
| *Expected Output:* `DATA VALIDATION AUDIT: PASS` |
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| --- |
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| ## 3. Representation Builders ($L_1$, $L_2$, $L_3$) |
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| ### Script 04: Build / Verify $L_1$ (Chunked Unstructured) |
| Splits knowledge records into 500-character recursive windows with overlap (4,526 agri, 4,202 legal, 892 edu chunks): |
| ```bash |
| python reproducibility/scripts/04_build_l1_chunks.py |
| ``` |
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| ### Script 05: Build / Verify $L_2$ (Full-Node Unstructured) |
| Concatenates all active schema fields with newline delimiters into an intact document per record (1,028 agri, 735 legal, 190 edu intact documents): |
| ```bash |
| python reproducibility/scripts/05_build_l2_full_nodes.py |
| ``` |
| |
| ### Script 06: Build / Verify $L_3$ (Structured BM25F) |
| Extracts records into dedicated indexed field slots according to the official schema (Appendix Table 7), tagging designated query-aligned anchor fields: |
| ```bash |
| python reproducibility/scripts/06_build_l3_fields.py |
| ``` |
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| --- |
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| ## 4. Design Principles |
| - **Standard Library Only**: All scripts run in standard Python 3.8+ without external dependencies. |
| - **Console Encoding Safe**: Automatic UTF-8 console reconfiguring prevents Windows cp1252 character errors. |
| - **Relocatable Execution**: Scripts automatically detect project root from `__file__` or accept explicit `--data_dir` and `--output_dir` arguments. |
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