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JCoRe Sentence Boundary Detection Analysis Engine

A machine learning based sentence boundary detector


JSBD is a ML-based sentence splitter. It can be retrained on supported training material and is thus neither language nor domain dependent.

Requirement and Dependencies

JTBD is based on a slightly modified version of the machine learning toolkit MALLET (Version 2.0.x). The necessary libraries are included in the executable JAR (see below) and accessible via the JULIE Nexus artifact manager.

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/ but it can be further edited if so desired; see UIMA SDK User's Guide for further information.

1. Parameters

Parameter Name Parameter Type Mandatory Multivalued Description
ModelFilename String yes no filename of trained model for JSBD
Postprocessing Boolean no no Indicates whether postprocessing should be run. Default: no postprocessing
ProcessingScope String no no The UIMA annotation type over which to iterate for doing the sentence segmentation. If nothing is given, the document text from the CAS is taken as scope! This is recommended as default!

2. Predefined Settings

Parameter Name Parameter Syntax Example
ModelFilename valid path to a model file de/julielab/jcore/ae/jsbd/model/jsbd-2.0.gz*
Postprocessing Boolean Variable true
ProcessingScope Boolean Variable none
* a model is not included; see the biomed-project fro a pre-built one

3. Capabilities

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


An extensive documentation can be found under doc/.

You can also run JSBD just via the self-executing JAR jsbd-<version>.jar. This will show the available modes.