# MedMentions: A Large Biomedical Corpus Annotated with UMLS Concepts

arXiv: https://arxiv.org/abs/1902.09476 · HTML: https://mlsanity.com/paper/1902.09476/

## Key facts

- Cited by 80 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Feb 2019.

## Built on by (most cited first, 30 of 80)

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- [Generative Biomedical Entity Linking via Knowledge Base-Guided Pre-training and Synonyms-Aware Fine-tuning](https://mlsanity.com/paper/2204.05164/) (2022)
- [AMMU : A Survey of Transformer-based Biomedical Pretrained Language Models](https://mlsanity.com/paper/2105.00827/) (2021)
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- [Data-Centric Foundation Models in Computational Healthcare: A Survey](https://mlsanity.com/paper/2401.02458/) (2024)
- [Entity Linking and Discovery via Arborescence-based Supervised Clustering](https://mlsanity.com/paper/2109.01242/) (2021)
- [BioLORD: Learning Ontological Representations from Definitions (for Biomedical Concepts and their Textual Descriptions)](https://mlsanity.com/paper/2210.11892/) (2022)
- [ECG-Image-Kit: A Synthetic Image Generation Toolbox to Facilitate Deep Learning-Based Electrocardiogram Digitization](https://mlsanity.com/paper/2307.01946/) (2023)
- [ReflecTool: Towards Reflection-Aware Tool-Augmented Clinical Agents](https://mlsanity.com/paper/2410.17657/) (2024)
- [Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutions](https://mlsanity.com/paper/2404.09135/) (2024)
- [Fast and Effective Biomedical Entity Linking Using a Dual Encoder](https://mlsanity.com/paper/2103.05028/) (2021)
- [Multimodal Large Language Models for Medicine: A Comprehensive Survey](https://mlsanity.com/paper/2504.21051/) (2025)
- [Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical Text](https://mlsanity.com/paper/2110.08228/) (2021)
- [BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Residual Convolutional Neural Networks](https://mlsanity.com/paper/2109.02237/) (2021)
- [TempEL: Linking Dynamically Evolving and Newly Emerging Entities](https://mlsanity.com/paper/2302.02500/) (2023)
- [A Search Engine for Discovery of Scientific Challenges and Directions](https://mlsanity.com/paper/2108.13751/) (2021)
- [SpEL: Structured Prediction for Entity Linking](https://mlsanity.com/paper/2310.14684/) (2023)
- [NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities](https://mlsanity.com/paper/2210.11913/) (2022)
- [Computer Science Named Entity Recognition in the Open Research Knowledge Graph](https://mlsanity.com/paper/2203.14579/) (2022)
- [Biomedical Language Models are Robust to Sub-optimal Tokenization](https://mlsanity.com/paper/2306.17649/) (2023)
- [On-the-fly Definition Augmentation of LLMs for Biomedical NER](https://mlsanity.com/paper/2404.00152/) (2024)
- [HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools](https://mlsanity.com/paper/2402.12372/) (2024)
- [KcMF: A Knowledge-compliant Framework for Schema and Entity Matching with Fine-tuning-free LLMs](https://mlsanity.com/paper/2410.12480/) (2024)
- [How Do Your Biomedical Named Entity Recognition Models Generalize to Novel Entities?](https://mlsanity.com/paper/2101.00160/) (2021)
- [Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linking](https://mlsanity.com/paper/2302.07189/) (2023)
- [Ontology Enrichment from Texts: A Biomedical Dataset for Concept Discovery and Placement](https://mlsanity.com/paper/2306.14704/) (2023)
- [BELB: a Biomedical Entity Linking Benchmark](https://mlsanity.com/paper/2308.11537/) (2023)

## Abstract (arXiv)

This paper presents the formal release of MedMentions, a new manually annotated resource for the recognition of biomedical concepts. What distinguishes MedMentions from other annotated biomedical corpora is its size (over 4,000 abstracts and over 350,000 linked mentions), as well as the size of the concept ontology (over 3 million concepts from UMLS 2017) and its broad coverage of biomedical disciplines. In addition to the full corpus, a sub-corpus of MedMentions is also presented, comprising annotations for a subset of UMLS 2017 targeted towards document retrieval. To encourage research in Biomedical Named Entity Recognition and Linking, data splits for training and testing are included in the release, and a baseline model and its metrics for entity linking are also described.