Add DATA_PROCESSING.md documentation

DATA_PROCESSING.md

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+# Data Processing Pipeline
+
+This document describes the technical workflow for constructing and maintaining the Nepali Text Corpus.
+
+## Overview
+
+The corpus is built using a DuckDB-based pipeline (`scripts/merge.py`) that ingests raw CSVs, applies filtering and normalization, and produces stratified parquet outputs optimized for different research domains.
+
+```
+Raw Data (CSV) → Validation & Normalization → Domain Stratification → Parquet Output
+```
+
+## Input Sources
+
+| Source | File | Format | Records | Notes |
+|--------|------|--------|---------|-------|
+| IRIISNEPAL | `iriisnepal_raw.csv` | CSV | ~6.1M | Manually curated formal Nepali |
+| YouTube | `youtube_comments_clean.csv` | CSV | ~431K | Pre-cleaned by `clean.py` |
+| Wikipedia | `wikipedia_nepali.csv` | CSV | ~291K | Extracted from wiki dump |
+| News | `nepali_news.csv` | CSV | ~87K | Scraped from live news feeds |
+
+## Preprocessing Steps
+
+### 1. Text Validation
+All records are filtered on:
+- **Non-null check:** `text IS NOT NULL`
+- **Non-empty check:** `trim(text) <> ''`
+- **Minimum length (IRIIS only):** `length(split(trim(text), ' ')) >= 5` (5+ words)
+- **Script validation (IRIIS only):** Must contain at least one Devanagari character
+
+### 2. Script Detection
+Automatic classification for news and YouTube sources:
+```
+IF text contains [ऀ-ॿ] THEN 'devanagari'
+ELSE IF text contains [A-Za-z] THEN 'latin'
+ELSE 'other'
+```
+
+### 3. Metadata Assignment
+Each row is enriched with:
+- **source:** Origin identifier (e.g., `iriisnepal`, `youtube_comments`, `wikipedia_nepali`)
+- **domain:** Content category (formal, colloquial, encyclopedia, news)
+- **script:** Writing system detected
+- **lang:** ISO 639-1 code (`ne` for Nepali)
+- **date_collected:** Processing date
+- **license:** Source-specific license
+
+### 4. Deduplication
+- No exact-duplicate removal (preserves all unique utterances)
+- Partial duplicates retained (colloquial speech naturally repeats common phrases)
+
+## Output Datasets
+
+### nepali_corpus_full.parquet
+**Purpose:** Complete merged corpus for general research  
+**Rows:** 7,167,456  
+**Ordering:**
+1. Formal domain (IRIISNEPAL)
+2. Encyclopedia domain (Wikipedia)
+3. News domain
+4. Colloquial domain (YouTube)
+
+Within each domain, ordered by `source`, then `length DESC` for visibility.
+
+### nepali_corpus_formal.parquet
+**Purpose:** Formal writing for LM pretraining  
+**Rows:** 6,378,206 (formal + encyclopedia + news)  
+**Domains included:** `formal`, `encyclopedia`, `news`  
+**Ordering:** Domain priority → source → length DESC
+
+**Professional dataset preview:** Leading rows are formal Wikipedia and news articles (clean, representative examples).
+
+### nepali_corpus_colloquial.parquet
+**Purpose:** Conversational Nepali for sociolinguistic analysis  
+**Rows:** 431,648 (YouTube comments only)  
+**Script distribution:**
+- Devanagari: 123,804 comments
+- Latin (Roman): 307,999 comments
+- Mixed: 19,845 comments
+
+**Ordering:** Devanagari (longest first) → Latin → Mixed (ensures Hugging Face viewer surfaces Devanagari examples first)
+
+### nepali_corpus_roman.parquet
+**Purpose:** Roman-script Nepali subset  
+**Rows:** 307,999 (latin script from YouTube)  
+**Derived from:** Colloquial corpus with `script = 'latin'`
+
+### nepali_corpus_wikipedia.parquet
+**Purpose:** Encyclopedia-style Nepali (NOT published separately; kept for analysis)  
+**Rows:** 291,767  
+**Note:** Wikipedia data is merged into `nepali_corpus_formal.parquet` for public release.
+
+## Performance Optimizations
+
+### DuckDB Configuration
+```sql
+PRAGMA threads = 2              -- CPU parallelism
+PRAGMA preserve_insertion_order = false
+PRAGMA memory_limit = '8GB'     -- RAM cap
+PRAGMA temp_directory = '...'   -- Disk spillover
+```
+
+### Parquet Compression
+- **Codec:** Zstandard (ZSTD)
+- **Compression Level:** Default (best balance)
+- **Result:** 5.95 GB file for 7.1M rows (≈850 bytes/row average)
+
+### Processing Speed
+- Typical merge run: ~2-5 minutes on 8GB RAM
+- DuckDB streaming keeps memory footprint constant
+
+## Quality Metrics
+
+### Content Representation
+- **Formal (88%):** Academic, journalistic, encyclopedic content
+- **Colloquial (6%):** Conversational, social media discourse
+- **Roman script (4%):** Transliterated Nepali
+- **Mixed script (<1%):** Code-switching examples
+
+### Text Statistics
+- **Average length:** ~120 UTF-8 characters
+- **Median length:** ~85 characters
+- **Max length:** ~50,000 characters (rare outliers)
+- **Devanagari percentage:** ~87% of rows
+
+### Coverage
+- **Unique sources:** 5 primary (IRIIS, Wikipedia, YouTube, Kantipur, Setopati, +3 others)
+- **Time span:** Circa 2016–2026 (mixed historical and current)
+- **Geographic scope:** Nepal-centric; diaspora content included in YouTube
+
+## Maintenance & Updates
+
+### Incremental Updates
+To add new data:
+1. Append new rows to source CSV (e.g., `nepali_news.csv`)
+2. Re-run `scripts/merge.py`
+3. Output parquets are regenerated from scratch
+4. Run `scripts/publish.py` to sync to Hugging Face
+
+### Re-running the Pipeline
+```bash
+cd /Users/ad/research/nepali-text
+venv/bin/python scripts/merge.py
+```
+
+## Schema Reference
+
+All parquet files use this schema:
+
+| Column | Type | Description |
+|--------|------|-------------|
+| text | string | UTF-8 Nepali text |
+| source | string | Data source identifier |
+| domain | string | Content type (formal, colloquial, encyclopedia, news) |
+| script | string | Writing system (devanagari, latin, mixed) |
+| lang | string | ISO 639-1 language code (always 'ne') |
+| date_collected | string | ISO 8601 processing date |
+| license | string | Source license (MIT, CC BY 4.0, CC BY-SA 4.0, source-dependent) |
+
+## Known Limitations
+
+1. **YouTube content:** No content filtering; raw comments may contain offensive language
+2. **News licensing:** Publisher permissions uncertain; use cautiously in commercial settings
+3. **Script detection:** Simple regex-based; mixed-language text occasionally misclassified
+4. **Deduplication:** No semantic deduplication; similar paraphrases retained
+5. **Temporal bias:** Majority of data from 2020–2026; pre-2020 IRIIS content underrepresented
+
+## Future Improvements
+
+- [ ] Semantic deduplication using embeddings
+- [ ] Fine-grained toxicity filtering for colloquial subset
+- [ ] Add date ranges per source for temporal filtering
+- [ ] Multilingual metadata (code-mixed Hindi, English)
+- [ ] Validation splits for supervised task benchmarking
+
+---
+
+**Last Updated:** April 2, 2026  
+**Pipeline Version:** 1.0  
+**Maintainer:** Boredoom17