Support from such tools could consist of highlighting key phrases, capturing detailed attributes within a phrase, or suggesting domain-specific annotations ( 1). It is therefore important to provide domain experts with the tools necessary to annotate unstructured text rapidly and accurately. We demonstrate a real-world use case of how Markup has been used in a healthcare setting to annotate structured information from unstructured clinic letters, where captured annotations were used to build and test NLP applications. Markup incorporates NLP and Active Learning (AL) technologies to enable rapid and accurate annotation using custom user configurations, predictive annotation suggestions, and automated mapping suggestions to both domain-specific ontologies, such as the Unified Medical Language System (UMLS), and custom, user-defined ontologies. We present Markup ( ) an open-source, web-based annotation tool that is undergoing continued development for use across all domains. Annotation tools can assist with this process by providing functionality that enables the accurate capture and transformation of unstructured texts into structured annotations, which can be used individually, or as part of larger Natural Language Processing (NLP) pipelines.
ANNOTATE ARTICLE MANUAL
However, the unstructured nature of free-text data poses a significant challenge for its utilisation due to the necessity of substantial manual intervention from domain-experts to label embedded information. These potential data sources often contain rich information that could be used for domain-specific and research purposes. 3Neurology Department, Morriston Hospital, Swansea Bay University Health Board, Swansea, United KingdomĪcross various domains, such as health and social care, law, news, and social media, there are increasing quantities of unstructured texts being produced.2Swansea University Medical School, Swansea University, Swansea, United Kingdom.1Health Data Research UK, Swansea University Medical School, Swansea University, Swansea, United Kingdom.Owen Pickrell 2,3, Beata Fonferko-Shadrach 2, Carys Jones 2, Ashley Akbari 1,2, Simon Thompson 1,2 and Arron Lacey 1,2 *
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