The Apache OpenNLP team is pleased to announce the release of Apache OpenNLP 3.0.0-M2.
The Apache OpenNLP library 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.
Apache OpenNLP 3.0.0-M2 binary and source distributions are available for download from our download page.
The OpenNLP library is distributed by Maven Central as well. See the Maven dependency page for more details.
The 3.x release line of Apache OpenNLP introduces no known breaking changes while significantly modularizing the project to improve library usage and future extensibility. The core API remains stable and fully compatible with 2.x, so existing projects can continue using the opennlp-tools artifact without modifications.
Key Highlights and Recommendations:
Notable Changes:
The minimum Java compiler level was raised to 21 (OPENNLP-1735)
The artifact 'opennlp-models' was renamed to 'opennlp-model-resolver'. It can be used to detect and load OpenNLP compliant models from the classpath (OPENNLP-1807)
New Features:
Apache OpenNLP can now detect sentiment from text (OPENNLP-855)
The eval corpus format for GermEval2014 is now supported (OPENNLP-976)
Document Categorization is now possible via a binding to LibSVM (OPENNLP-1808)
Bug Fixes:
The SentenceDetector got three fixes in handling edge cases with abbreviation dictionaries (OPENNLP-1809, OPENNLP-1810, OPENNLP-1811) - NOTE: These fixes have been back-ported to OpenNLP 2.5.8.
Improvements:
Language Codes passed in are now stricter validated to comply with ISO-693 standard (OPENNLP-991)
The OpenNLP developer manual (HTML + PDF) got an uplift for the UIMA documentation part, being largely extended (OPENNLP-49)
For further details, check the full list of changes via the project’s issue tracker.
The 3.x release line of Apache OpenNLP upgrades the compiler level to Java 21 and modularizes the project for better usage as a library and to support future extensibility. The core API remains stable and compatible with 2.x, but the project structure has been reorganized into multiple modules.
That means, that you can continue to use the previous opennlp-tools artifact as a dependency. However, we strongly recommend to switch to the new modular structure and import only the components you need, which will result in a smaller dependency footprint.
Only opennlp-runtime needs to be added as a dependency, and you can add additional modules (e.g. opennlp-ml-maxent, opennlp-models, etc.) as required by your project. For users of the traditional CLI toolkit, nothing changes with the 3.x release line. CLI usage remains stable
--The Apache OpenNLP Team
31 March 2026