Basic language processing

Under basis language processing, we understand part-of-speech tagging, lemmatization, named entity recognition, chunking and similar tasks which label individual words.

Frog

Frog is an integration of memory-based natural language processing (NLP) modules developed for Dutch. Frog's current version will tokenize, tag, lemmatize, and morphologically segment word tokens in Dutch text files, will assign a dependency graph to each sentence, will identify the base phrase chunks in the sentence, and will attempt to find and label all named entities.

• Online version
• Project website

DeepFrog

DeepFrog aims to be a (partial) successor of the Dutch-NLP suite Frog. Whereas the various NLP modules in Frog were built on k-NN classifiers, DeepFrog builds on deep learning techniques and can use a variety of neural transformers.

• POS tagger

The system is not yet officially released.

• Github page

LeTs

LeTs is preprocessor that can be used for Dutch, German, English and French.

• Project page
• Demo

Spacy

Dutch models

Stanza - A Python NLP Package for Many Human Languages

Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages.

• Stanza github pages

Trankit

Trankit is a light-weight Transformer-based Python Toolkit for multilingual Natural Language Processing (NLP). It provides a trainable pipeline for fundamental NLP tasks over 100 languages, and 90 downloadable pretrained pipelines for 56 languages.

• Trankit Github pages

Adelheid Tagger-Lemmatizer: A Distributed Lemmatizer for Historical Dutch

With this web-application an end user can have historical Dutch texts tokenized, lemmatized and part-of-speech tagged, using the most appropriate resources (such as lexica) for the text in question. For each specific text, the user can select the best resources from those available in CLARIN, wherever they might reside, and where necessary supplemented by own lexica.

• CLAPOP page
• No working version found