# REE-HDSC: Recognizing Extracted Entities for the Historical Database Suriname Curacao

arXiv: https://arxiv.org/abs/2401.02972 · HTML: https://mlsanity.com/paper/2401.02972/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 16 references that are in the map.
- First posted on arXiv 19 Dec 2023.

## Builds on (most cited first, 2 of 2)

- [What's so special about BERT's layers? A closer look at the NLP pipeline in monolingual and multilingual models](https://mlsanity.com/paper/2004.06499/) (2020)
- [READ-BAD: A New Dataset and Evaluation Scheme for Baseline Detection in Archival Documents](https://mlsanity.com/paper/1705.03311/) (2017)

## Abstract (arXiv)

We describe the project REE-HDSC and outline our efforts to improve the quality of named entities extracted automatically from texts generated by hand-written text recognition (HTR) software. We describe a six-step processing pipeline and test it by processing 19th and 20th century death certificates from the civil registry of Curacao. We find that the pipeline extracts dates with high precision but that the precision of person name extraction is low. Next we show how name precision extraction can be improved by retraining HTR models with names, post-processing and by identifying and removing incorrect names.