We present our work on aligning the Unified Medical Language System (UMLS) to
Wikipedia, to facilitate manual alignment of the two resources. We propose a
cross-lingual neural reranking model to match a UMLS concept with a Wikipedia
page, which achieves a recall@1 of 72%, a substantial improvement of 20% over
word- and char-level BM25, enabling manual alignment with minimal effort. We
release our resources, including ranked Wikipedia pages for 700k UMLS concepts,
and WikiUMLS, a dataset for training and evaluation of alignment models between
UMLS and Wikipedia. This will provide easier access to Wikipedia for health
professionals, patients, and NLP systems, including in multilingual settings.

使用跨语言神经重排序模型对统一医学语言系统和维基百科进行手动对齐，精确度高达 72％，比基于词和字符级别的 BM25 方法提高了 20％。我们发布了相关资源，包括为 70 万个统一医学语言系统概念排序的维基百科页面，并提供了一个可用于训练和评估的统一医学语言系统和维基百科对齐模型数据集。这将在多种语言环境下为医疗专业人士、患者和自然语言处理系统提供更容易访问维基百科的方式。