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JCoRe Acronym Analysis Engine

This is a reimplementation of the Schwartz and Hearst Algorithm for the resolution of acronyms (short form → long form).

Descriptor Path:



JULIE Lab Acronym Annotator (JACRO) is an UIMA Analysis Engine that annotates acronyms with their full-forms when locally introduced in the current document. The functionality of the engine is based on the simple algorithm for abbreviation recognition by Schwartz and Hearst. We have reimplemented the algorithm and extended it with respect to some pattern definitions and normalizations. During the processing of documents, this UIMA annotator takes jcore.types.Sentence annotions from the CAS and creates an jcore.types.Abbreviation annotation object for each identified acronym. The jcore.types.Abbreviation annotation stores the corresponding full-form, whether the acronym was introduced at the respective position, and a reference to the full-form in the text.

Requirement and Dependencies

The input and output of an AE is done via annotation objects. The classes corresponding to these objects are part of the JCoRe Type System.

Using the AE - Descriptor Configuration

In UIMA, each component is configured by a descriptor in XML. Such a preconfigured descriptor is available under src/main/resources/de/julielab/jcore/ae/acronymtagger/desc but it can be further edited if so desired; see UIMA SDK User's Guide for further information. The import by name location of the default descriptor is


1. Parameters

Parameter Name Parameter Type Mandatory Multivalued Description
ConsistencyAnno Boolean yes no specifies whether only the first or all occurences of the acronym are annotated in the document
MaxLength Integer yes no defines how far (how many words, ignoring stopwords) the AE is supposed to look for the beginning of the fullform

2. Predefined Settings

Parameter Name Parameter Syntax Example
ConsistencyAnno set to true if you want to annotate all occurences of the acronyms that were found true
MaxLength just an integer 5

3. Capabilities

Type Input Output
de.julielab.jcore.types.Sentence +
de.julielab.jcore.types.Abbrevation +


Ariel S. Schwartz and Marti H. Hearst. 2003. A simple algorithm for identifying abbreviation definitions in biomedical text. In Russ B. Altman, A. Keith Dunker, Lawrence Hunter, Tiffany A. Jung, and Teri E. Klein, editors, PSB 2003 – Proceedings of the Pacific Symposium on Biocomputing 2003. Kauai, Hawaii, USA, January 3-7, 2003, pages 451–462.