# E211 Phase 1 Findings — VOC-ArchNLP Pilot Extraction

**Date:** 2026-04-23
**Pipeline:** VOC-ArchNLP v1.0.0 (HKI Hak Cipta 2026)
**Corpus:** 500 GLOBALISE files, 548,929 paragraphs, 145,971,146 words
**Status:** PHASE 1 COMPLETE — methodologically informative negative result

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## Raw Extraction Results

| Metric | Value |
|---|---|
| Files processed | 500 |
| Paragraphs | 548,929 |
| Words | ~146 million |
| Total candidate mentions | 33,930 |
| With depth measurement | 91 |
| After Java/Indonesia geographic filter | 14,626 (43.1%) |
| Java + MONUMENT + INSCRIPTION | 871 |
| "oudheden/oudheidkundig" (archaeological vocabulary) | **0** |

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## Quality Assessment — False Positive Analysis

### Critical false positives identified

| Keyword | Intended meaning | Actual meaning in corpus | FP rate est. |
|---|---|---|---|
| `pagode` | Temple/pagoda | Dutch gold coin (unit of currency in South Asian trade) | >95% |
| `arca` | Javanese statue | Latin/Portuguese/Spanish "arca" = chest/box/ark | ~100% |
| `opschrift` | Archaeological inscription | Any document heading or label | >90% |
| `vervallen` | Ruins, collapsed | Administrative: expired/lapsed; fell into | >80% |
| `Candi` | Javanese temple | Place name = Kandy, Kingdom of Sri Lanka | ~80% |
| `graven` | Burial/grave | Verb: to dig (moats, canals, foundations) | ~70% |
| `pura` | Balinese temple | Place name component (Singapura → "Singa pura") | ~80% |

### What was NOT found (informative absence)

- `oudheden` / `oudheidkundig` = 0 occurrences → No Dutch archaeological vocabulary in this corpus
- `prasasti` = 0 (genuine) → VOC administrators did not use Javanese loanword for inscriptions  
- `stupa` = 0 genuine → Buddhist monument vocabulary absent
- Depth + archaeological = 34 (Java context), but most are construction/military, not burial

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## Scientific Interpretation

### Finding F1: VOC dagregisters ≠ archaeological reports

The 500-file pilot corpus (inventory numbers 1074–10119, broadly 1602–1700s) consists of:
- Trade correspondence and records
- Political/military dispatches
- Navigation logs
- Administrative decisions

These document types were NOT vehicles for archaeological observation. The Dutch colonial authorities did not systematically document pre-Islamic monuments until the 18th–19th century (OV era, 1920s–1940s).

**Implication:** The VOLCARCH archaeological signal is NOT significantly present in the early VOC dagregisters tested. The Delpher (1854–1942) and OV (1925–1949) corpora have higher precision because they were specifically oriented toward colonial administration of cultural heritage.

### Finding F2: "Pagode" as currency = dominant false positive

The VOC administered trade denominated in "pagode" (South Indian gold coin). This word appears thousands of times in trade records and swamps any genuine temple references. The word "pagode" as temple/pagoda is the modern/later meaning; in 17th-century Dutch commercial contexts, it was overwhelmingly a currency unit.

**Implication:** Keyword lexicons for historical NLP must account for polysemy that is era-specific and domain-specific. A word's modern meaning may be its MINORITY meaning in the target corpus.

### Finding F3: "Arca" cross-language collision

The Javanese/Sanskrit "arca" (sacred statue/image) is identical in form to the Latin/Portuguese/Spanish "arca" (chest, box, ark — as in Ark of the Covenant). The VOC corpus contains substantial Portuguese/Spanish/Latin material from early contact documents. Every "arca" hit is a false positive from this cross-language collision.

**Implication:** Language identification is required before entity-level keyword matching in a multilingual colonial corpus. The early VOC records contain Dutch, Portuguese, Spanish, Latin, Malay, and Japanese text.

### Finding F4: Genuine signal exists but requires deeper mining

Despite the precision issues, the corpus DID yield:
- 34 Java-context depth measurements (requiring annotation to verify archaeological relevance)
- ~664 Java-context MONUMENT candidates (after pagode/Candi FP removal: probably ~50–100 genuine)
- Some genuine grave mentions ("dooden ontgraven" = dead exhumed, "begraven" in genuine burial context)

The signal is present but at low density, requiring NER to separate from trade/administrative noise.

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## Comparison with Prior Experiments

| Experiment | Corpus | Method | Recall | Precision |
|---|---|---|---|---|
| E091 | OV 1925–1949 | Rule-based NLP | HIGH | HIGH (domain-specific) |
| E141 | Delpher 1854–1942 | Keyword + KB SRU | MEDIUM | MEDIUM |
| **E211 Phase 1** | **VOC 1600s–1700s** | **Keyword matching** | **HIGH** | **LOW (<15% est.)** |
| E211 Phase 2 (planned) | VOC 1600s–1700s | NER fine-tuned | — | Target: >60% |

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## Revised Pipeline Requirements for Phase 2

Based on Phase 1 findings, the following must be added before Phase 2 annotation:

1. **Language detection** — filter non-Dutch paragraphs (Portuguese, Latin, Spanish, Malay)
2. **Currency context filter** — exclude "pagode" when followed by price/quantity patterns
3. **Geographic precision filter** — require Java/Indonesian place name within 200 tokens
4. **"Candi" disambiguation** — differentiate Javanese temple from Kingdom of Kandy
5. **"arca" disambiguation** — language-based: Latin/Spanish/Portuguese = chest, Indonesian = statue
6. **Negation filter** — "vervallen" must occur as adjective (ruinous), not as verb (lapsed)

These filters will reduce the 33,930 → estimated ~500–1,000 true positives, with precision >60%.

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## Normalization Impact (Post-normalize extraction)

| Metric | Pre-normalize | Post-normalize | Delta |
|---|---|---|---|
| Total mentions | 33,930 | 33,931 | +1 |
| MONUMENT | 1,982 | 1,983 | +1 (tjandi→candi) |
| With depth | 91 | 92 | +1 |
| Precision | <15% est. | <15% est. | No change |

**Conclusion:** Normalization has negligible impact on keyword extraction precision/recall. The fundamental false-positive problem (pagode = currency, arca = chest) is domain-semantic, not orthographic — normalization cannot fix it. Normalization is valuable for downstream NER and geocoding (consistent place names, expanded abbreviations) but does not solve Phase 1 precision.

## Place Name Co-occurrence (high-precision mentions)

Top Java locations co-occurring with MONUMENT+INSCRIPTION mentions (871 rows):
- Batavia: 407 | Banten: 107 | Java: 70 | Jepara: 41 | Mataram: 11 | Semarang: 11

**Geographic bias:** Batavia (=Jakarta) dominates — expected since VOC correspondence was centralized there. Archaeological-quality MONUMENT mentions from interior Java (Kediri, Trowulan, Singosari) = 0 in this 500-file pilot. This supports F1 (early dagregisters don't cover interior Java systematically).

## Status

- **Phase 1 (preprocessing + keyword extraction):** COMPLETE (2026-04-23)
- **Phase 2 (annotation + NER fine-tuning):** PENDING — 65-sentence annotation sample ready at `results/E211_voc_mentions/annotation_sample_v1.csv`; guide at `results/E211_voc_mentions/ANNOTATION_GUIDE_v1.md`
- **Phase 3 (geocoding):** BLOCKED on Phase 2 precision
- **Phase 4 (analysis + paper):** BLOCKED on Phase 3

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## Output Files

| File | Description | Rows |
|---|---|---|
| `results/E211_voc_mentions/voc_archaeological_mentions.csv` | Full extraction, all types | 33,930 |
| `results/E211_voc_mentions/voc_mentions_java_filtered.csv` | Java/Indonesia context only | 14,626 |
| `results/E211_voc_mentions/voc_mentions_high_precision.csv` | MONUMENT+INSCRIPTION, Java | 871 |
| `results/E211_voc_mentions/voc_archaeological_mentions.json` | Full extraction (JSON) | 33,930 |
| `results/E211_voc_mentions/pipeline_summary.json` | Stage statistics | — |

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## Contribution to VOLCARCH

**Positive:** Confirms that the OV/Delpher period (1854–1949) is more data-rich for VOLCARCH validation than the early VOC dagregisters. This refines the temporal strategy — focus E211 Phase 2 on later GLOBALISE files (18th-century volumes where colonial archaeology vocabulary emerges).

**Methodological:** Demonstrates why domain-specific fine-tuned NER is non-negotiable for historical colonial Dutch text mining. This is the core motivation for Phase 2 and the primary contribution of the eventual E211 paper.

**Dataset:** The 33,930 candidate sentences represent a valuable annotation-ready corpus for training historical NLP models, even if the precision is low. This is itself a contribution to the field.

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*E211 Phase 1 findings documented 2026-04-23. Next: Phase 2 annotation protocol.*