NLP-Cube

Why we included this project

NLP-Cube bundles the usual preprocessing chain (sentence splitting, tokenization, lemmatization, part-of-speech tagging, and dependency parsing) into one pipeline that emits standard CoNLL-U, so the output drops straight into downstream NLP or information-extraction work. It ships with pretrained models for the languages covered by Universal Dependencies treebanks, and the Python API is small: load a language, annotate a document, and read per-token attributes like lemma, UPOS, XPOS, and dependency head. Because everything follows the UD annotation scheme, it suits research or production pipelines that want consistent, standards-compliant annotations across many languages. If the bundled models do not fit your domain, the advanced tutorials walk through training your own.