NLPprojektis

NLPprojektis is a modular, open-source framework and collection of tools for natural language processing. It is designed to support both research and production applications by providing components for data processing, model development, evaluation, and deployment. The project emphasizes language-agnostic design, reproducibility, and extensibility through a plugin system. It originated from a collaboration among universities and industry labs aiming to lower barriers to building NLP systems.

The core of NLPprojektis consists of interoperable components for end-to-end NLP pipelines: data loaders, tokenizers, lemmatizers, part-of-speech taggers, dependency parsers, named entity recognizers, sentiment analyzers, and modules for summarization or machine translation. The architecture supports pipelines, batch processing, and streaming data, with a standard interface for models and datasets. A plugin registry allows swapping models and adapters to popular machine learning frameworks.

Data handling and evaluation are central to the project. NLPprojektis provides a model zoo, evaluation benchmarks, and configuration-driven experiment tracking to improve reproducibility. It supports multilingual resources and low-resource languages, with guidelines for licensing, data provenance, and privacy-preserving practices.

Development and governance are community-driven. The project is maintained by researchers and developers across institutions, with open contribution guidelines, code of conduct, and transparent decision-making processes. Code and data licenses are documented to clarify usage rights and redistribution terms.

In practice, NLPprojektis is used in academic research, prototype deployments, and industry pilots. It aims to standardize interfaces and evaluation, while remaining adaptable to new models and tasks. As with any NLP toolkit, performance varies by language and domain and depends on data quality and task formulation.