# HERITAGE: An End-to-End Web Platform for Processing Korean Historical Documents in Hanja

arXiv: https://arxiv.org/abs/2501.11951 · HTML: https://mlsanity.com/paper/2501.11951/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 29 references that are in the map.
- First posted on arXiv 21 Jan 2025.

## Builds on (most cited first, 11 of 11)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Efficient Memory Management for Large Language Model Serving with PagedAttention](https://mlsanity.com/paper/2309.06180/) (2023)
- [LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://mlsanity.com/paper/2403.13372/) (2024)
- [AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration](https://mlsanity.com/paper/2306.00978/) (2023)
- [Named Entity Recognition and Classification on Historical Documents: A Survey](https://mlsanity.com/paper/2109.11406/) (2021)
- [Restoring and Mining the Records of the Joseon Dynasty via Neural Language Modeling and Machine Translation](https://mlsanity.com/paper/2104.05964/) (2021)
- [HistRED: A Historical Document-Level Relation Extraction Dataset](https://mlsanity.com/paper/2307.04285/) (2023)
- [Translating Hanja Historical Documents to Contemporary Korean and English](https://mlsanity.com/paper/2205.10019/) (2022)
- [HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea](https://mlsanity.com/paper/2210.05112/) (2022)
- [SanskritShala: A Neural Sanskrit NLP Toolkit with Web-Based Interface for Pedagogical and Annotation Purposes](https://mlsanity.com/paper/2302.09527/) (2023)
- [Shared Heritage, Distinct Writing: Rethinking Resource Selection for East Asian Historical Documents](https://mlsanity.com/paper/2411.04822/) (2024)

## Built on by (most cited first, 2 of 2)

- [Do Evaluation Metrics Detect Errors in Classical Chinese to English Translations?](https://mlsanity.com/paper/2608.08283/) (2026)
- [When the Knowledge Base Becomes the Gold Standard: Measuring Resource-Shared Evaluation Loops in Entity-Level Machine Translation](https://mlsanity.com/paper/2608.11843/) (2026)

## Abstract (arXiv)

While Korean historical documents are invaluable cultural heritage, understanding those documents requires in-depth Hanja expertise. Hanja is an ancient language used in Korea before the 20th century, whose characters were borrowed from old Chinese but had evolved in Korea for centuries. Modern Koreans and Chinese cannot understand Korean historical documents without substantial additional help, and while previous efforts have produced some Korean and English translations, this requires in-depth expertise, and so most of the documents are not translated into any modern language. To address this gap, we present HERITAGE, the first open-source Hanja NLP toolkit to assist in understanding and translating the unexplored Korean historical documents written in Hanja. HERITAGE is a web-based platform providing model predictions of three critical tasks in historical document understanding via Hanja language models: punctuation restoration, named entity recognition, and machine translation (MT). HERITAGE also provides an interactive glossary, which provides the character-level reading of the Hanja characters in modern Korean, as well as character-level English definition. HERITAGE serves two purposes. First, anyone interested in these documents can get a general understanding from the model predictions and the interactive glossary, especially MT outputs in Korean and English. Second, since the model outputs are not perfect, Hanja experts can revise them to produce better annotations and translations. This would boost the translation efficiency and potentially lead to most of the historical documents being translated into modern languages, lowering the barrier on unexplored Korean historical documents.