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. These tasks are usually required to build more advanced text processing services. OpenNLP also includes maximum entropy and perceptron based machine learning.
References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Taylor B. Arnold: A Tidy Data Model for Natural Language Processing using cleanNLP (2017) arXiv
- Yu, Hsiang-Fu; Huang, Fang-Lan; Lin, Chih-Jen: Dual coordinate descent methods for logistic regression and maximum entropy models (2011)