DKPro Lab

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 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.


The source code is provided under the Apache Software License (ASL) version 2.


Additional Attributes


Identifying Argumentative Discourse Structures in Persuasive Essays

Christian Stab, Iryna Gurevych
In: Conference on Empirical Methods in Natural Language Processing (EMNLP 2014), p. 46-56, October 2014
Association for Computational Linguistics

Hierarchy Identification for Automatically Generating Table-of-Contents

Nicolai Erbs, Iryna Gurevych, Torsten Zesch
In: Proceedings of 9th Conference on Recent Advances in Natural Language Processing (RANLP 2013), p. 252-260, September 2013

A Lightweight Framework for Reproducible Parameter Sweeping in Information Retrieval

Richard Eckart de Castilho, Iryna Gurevych
In: Proceedings of the 2011 workshop on Data infrastructurEs for supporting information retrieval evaluation, p. 7-10, 2011
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