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Graveyard Keeper 2 Mod
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LOCALIZATION MOD
RELEASED vrc-1 Austronesian Lang

Graveyard Keeper 2 Mod Graveyard Keeper 2 Mod

Bahasa Indonesia, Melayu, Filipino

Unduh mod lokalisasi Graveyard Keeper 2 Bahasa Indonesia terdahsyat dengan AI 8-tahap yang penuh komedi gelap, bahasa gaul, dan candaan sarkas!

Product Narrative

The Full Story

Graveyard Keeper 2 membawamu kembali ke persimpangan gelap yang konyol, di mana mengurus mayat, memberikan khotbah, dan berdebat dengan tengkorak cerewet bernama Larry adalah rutinitas biasa. Sebagai Penjaga Makam yang kelelahan, kamu harus bertahan hidup di dunia aneh ini sambil menghadapi warga desa yang banyak maunya, sekte misterius, dan aktivitas crafting yang gak ada habisnya. Ceritanya super luas dan komedi gelapnya benar-benar gila. Karena terjemahan kaku itu membosankan, kami merombak total 55.042 kata di game ini pakai pipeline neural 8-tahap buatan kami sendiri! Hasilnya? Gaya bicara The Keeper yang capek banget kerja, mulut pedas Larry yang super sarkas, sampai obrolan warga lokal semuanya diterjemahkan dengan bahasa gaul yang luwes. Perlu dicatat, mod ini masih tahap Alpha Eksperimental dan ada watermark preview. Kalau ada dialog yang aneh pas kamu lagi ngurus kuburan, langsung kasih tahu kami biar bisa diperbaiki di update selanjutnya!

Current Milestone

Available Now

Author's Notes

=== Audit Teknis & Semantik Lokalisasi GRAVEYARD KEEPER 2 === 1. SKALA LINGUISTIK & CAKUPAN - Skala Proyek: Sekitar 55,042 kata diproses melalui alur neural 8-tahap. - Cakupan Bahasa: Dukungan trilingual penuh untuk pasar Indonesia, Malaysia, dan Filipina. - Status Build: Experimental Alpha — watermarked preview build. - Status Kelengkapan: Indonesia: 98.5%, Malay: 98.9%, Filipino: 96.3% - Analisis Variasi Leksikal: Source -> Density: 63.2% | Diversity: 7.7%, Indonesia -> Density: 71.3% | Diversity: 11.6%, Malay -> Density: 73.0% | Diversity: 9.7%, Filipino -> Density: 59.2% | Diversity: 9.9% 2. VALIDASI NEURAL & AKURASI - Skor Keselarasan Semantik (Platt Score): (Skor ini mengukur seberapa akurat terjemahan mempertahankan makna asli dari teks sumber.) - Gaya Bahasa Karakter: Penyesuaian gaya (gaul, formal, santai) telah diterapkan pada 43 karakter unik. - Pemulihan Struktur Otomatis (Tag Repair): 13 tag kode game telah dipulihkan secara presisi. 3. KAPABILITAS ENGINE - Pipeline: Austronesian Localization System (Neural LoRA-Adaptive Architecture). - Pengenalan Entitas: Ekstraksi penuh untuk terminologi spesifik game dan konstanta lore.

Comments

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Linguistic Analysis Report

Stylometric Register Analysis

Discourse analysis using Gemma embeddings. Classifies rhetorical register across the corpus to ensure tonal consistency with source narrative assets.

Casual
55.8%
Standard
29.9%
Formal
14.3%
Emotional Spectrum

Emotional tone mapped via dot-product similarity between extracted dialog embeddings and predefined sentiment anchors using zero-shot semantic alignment.

Stoic/Restrained
29.9%
Neutral/Functional
26.0%
Positive/Warm
20.3%
Complex/Ambivalent
18.5%
Negative/Intense
5.2%
Archetypes
30 detected
The Keeper
27.3%
Ui/system
25.0%
Larry
5.9%
Jack
4.1%
Herbert
3.9%
Gunter
3.8%
Aghata
3.5%
Albert
3.3%
Linda
2.9%
Old God
2.3%
Npc Soldier
1.6%
Jully
1.4%
Januarius
1.2%
Comrade Donkey
1.1%
Soul
1.0%
Npc Guard
1.0%
Davy Dagger
0.9%
Bishop
0.9%
Goddess Of Nature
0.8%
Hans
0.6%
Sven
0.6%
Herm
0.6%
Trademaster
0.6%
Ambient Character
0.5%
Npc Scout
0.4%
Royal Mailbox
0.4%
Heffry
0.4%
Alter Keeper
0.4%
Dig
0.4%
Jeffry
0.4%

DISCLOSURE: Profiling data generated algorithmically via zero-shot inference and semantic vector alignment. Represents AI interpretation of the dataset corpus, not explicit ground-truth statistics from the underlying game engine or internal metrics. Use as a heuristic guide for context mapping.

Cross-Lingual Quality Matrix

Semantic alignment quantified via Multilingual E5 Large Instruct (RoBERTa based) bitext mining. NER entities preserved using GLiNER heuristic extraction protocols to maintain terminological invariance.

ID
Indonesian
6,401 / 6,501 lines
98%
Lex. Density
71.3 %
src
63.2%
Lex. Diversity
11.6 %
src
7.7%
MS
Malay
6,429 / 6,501 lines
99%
Lex. Density
73.0 %
src
63.2%
Lex. Diversity
9.7 %
src
7.7%
TL
Tagalog
6,258 / 6,501 lines
96%
Lex. Density
59.2 %
src
63.2%
Lex. Diversity
9.9 %
src
7.7%

* Sim = Cosine Similarity (Vector Space) · Density = Content/Total Tokens · Diversity = TTR (Type-Token Ratio) · "src" = Source Baseline · Named Entities enforced via GLiNER mining.

Corpus Volume & Metrics
18,726 Token Lines
Src Density
63.2%
Src Diversity
7.7%
Syntactic Error Report

Heuristic markup verification utilizing multi-pass validation and correction to ensure syntactical integrity of control codes and visual tags.

13
Mismatch
13
Fixed
0
Partial

Name

Label
Retrieving Portrait...
Narrative Profile

Associated Entities
Semantic Archetypes

NLP Pipeline Intelligence

Featured Preview Auto-Detected

Line Identity 0
Source (English)
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Indonesian (ID)
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Malay (MS)
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Tagalog (TL)
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Pipeline Receipts

Merger (S7) 2026-09-26 17:03
Tag Repair (S6) 2026-09-26 06:57
Re-Import (S4) 2026-09-26 06:44
Corrector (S3) 2026-09-26 06:33
Translator (S2) 2026-09-26 02:25
Tagger (S1) 2026-09-25 21:28
Splitter (S0) 2026-09-25 19:36

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