# FRASIMED: a Clinical French Annotated Resource Produced through Crosslingual BERT-Based Annotation Projection

arXiv: https://arxiv.org/abs/2309.10770 · HTML: https://mlsanity.com/paper/2309.10770/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 30 references that are in the map.
- First posted on arXiv 19 Sep 2023.

## Builds on (most cited first, 9 of 9)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Language-agnostic BERT Sentence Embedding](https://mlsanity.com/paper/2007.01852/) (2020)
- [Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation](https://mlsanity.com/paper/1808.07048/) (2018)
- [When and Why is Document-level Context Useful in Neural Machine Translation?](https://mlsanity.com/paper/1910.00294/) (2019)
- [Entity Projection via Machine Translation for Cross-Lingual NER](https://mlsanity.com/paper/1909.05356/) (2019)
- [Rethinking Document-level Neural Machine Translation](https://mlsanity.com/paper/2010.08961/) (2020)
- [X-SRL: A Parallel Cross-Lingual Semantic Role Labeling Dataset](https://mlsanity.com/paper/2010.01998/) (2020)
- [Cross-lingual Annotation Projection for Semantic Roles](https://mlsanity.com/paper/1401.5694/) (2014)
- [Cross-Lingual Transfer of Semantic Roles: From Raw Text to Semantic Roles](https://mlsanity.com/paper/1904.03256/) (2019)

## Built on by (most cited first, 6 of 6)

- [MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs](https://mlsanity.com/paper/2505.19800/) (2025)
- [FRACCO: A gold-standard annotated corpus of oncological entities with ICD-O-3.1 normalisation](https://mlsanity.com/paper/2510.13873/) (2025)
- [PARHAF, a human-authored corpus of clinical reports for fictitious patients in French](https://mlsanity.com/paper/2603.20494/) (2026)
- [Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus](https://mlsanity.com/paper/2604.06903/) (2026)
- [OntoBook: Ontology-Grounded Synthetic Textbooks for Medical Encoder Pretraining](https://mlsanity.com/paper/2607.18927/) (2026)
- [Cross-Lingual Clinical Annotation Projection as Constrained Text Generation: A Six-Language Study](https://mlsanity.com/paper/2609.11450/) (2026)

## Abstract (arXiv)

Natural language processing (NLP) applications such as named entity recognition (NER) for low-resource corpora do not benefit from recent advances in the development of large language models (LLMs) where there is still a need for larger annotated datasets. This research article introduces a methodology for generating translated versions of annotated datasets through crosslingual annotation projection. Leveraging a language agnostic BERT-based approach, it is an efficient solution to increase low-resource corpora with few human efforts and by only using already available open data resources. Quantitative and qualitative evaluations are often lacking when it comes to evaluating the quality and effectiveness of semi-automatic data generation strategies. The evaluation of our crosslingual annotation projection approach showed both effectiveness and high accuracy in the resulting dataset. As a practical application of this methodology, we present the creation of French Annotated Resource with Semantic Information for Medical Entities Detection (FRASIMED), an annotated corpus comprising 2'051 synthetic clinical cases in French. The corpus is now available for researchers and practitioners to develop and refine French natural language processing (NLP) applications in the clinical field (https://zenodo.org/record/8355629), making it the largest open annotated corpus with linked medical concepts in French.