3 projects tagged "UIMA"
Apache OpenNLP is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks are usually required to build more advanced text processing services.
uimaFIT provides Java annotations for describing UIMA components which can be used to directly describe the UIMA components in Java code without the need for traditional UIMA XML descriptors. This greatly simplifies refactoring a component definition (e.g., changing a configuration parameter name). uimaFIT also makes it easy to instantiate UIMA components without using XML descriptor files by providing convenient factory methods. This makes uimaFIT an ideal library for testing UIMA components because the component can be easily instantiated and invoked without requiring a descriptor file to be created first. uimaFIT is very useful in research environments in which programmatic/dynamic instantiation of UIMA pipelines can simplify experimentation. For example, when performing 10-fold cross-validation across a number of experimental conditions, it can be quite laborious to create a different set of descriptor files for each run, or even a script which generates such descriptor files. uimaFIT is type system agnostic and does not depend on (or provide) a specific type system.
DKPro Core is a collection of software components for natural language processing (NLP) based on the Apache UIMA framework. Many powerful and state-of-the-art NLP components are already freely available in the NLP research community. New and improved components are being developed and released continuously. The components cover the whole range of NLP-related processing tasks. DKPro Core provides wrappers for such third-party tool as well as original NLP components. DKPro Core builds heavily on uimaFIT which allows for rapid and easy development of NLP processing pipelines.