Apache UIMA is an Apache-licensed open source implementation of the UIMA specification (that specification is, in turn, being developed concurrently by a technical committee within OASIS, a standards organization). We invite and encourage you to participate in both the implementation and
... [More] specification efforts.
UIMA is a component framework for analysing unstructured content such as text, audio and video. It comprises an SDK and tooling for composing and running analytic components written in Java and C++, with some support for Perl, Python and TCL. [Less]
TreeTagger for Java is a Java wrapper around the popular TreeTagger package by Helmut Schmid. It was written with a focus on platform-independence and easy integration into applications. It is written in Java 5 and has been tested on OS X, Ubuntu Linux, and Windows.
uimaFIT is now part of the Apache UIMA project and is tracked there.
uimaFIT provides Java annotations to describe UIMA components in code without the need for XML descriptors, which simplifies refactoring definitions. uimaFIT makes it easy to instantiate UIMA components without using XML
... [More] descriptors by providing convenient factory methods. uimaFIT is type system agnostic and does not depend on (or provide) a type system.
uimaFIT an ideal library for testing UIMA components. It is useful in research environments in which programmatic instantiation of UIMA pipelines simplify experimentation. For example, when performing cross-validation across a number of experimental conditions, it is tedious to create XML descriptors for each run. [Less]
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
... [More] 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. [Less]
DKPro Lab is a lightweight framework for parameter sweeping experiments. It allows to set up experiments consisting of multiple interdependent tasks in a declarative manner with minimal overhead. Parameters are injected into tasks using via annotated class fields. Data produced by a task for any
... [More] particular parameter configuration is stored and re-used whenever possible to avoid the needless recalculation of results. Reports can be attached to each task to post-process the experimental results and present them in a convenient manner, e.g. as tables or charts. [Less]
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