opennlp vs corenlp : Market reach - popularity

Question

I am just doing the comparative study of open source NLP tools, and got an idea about the features/services of openNLP and coreNLP engines. In the recent past, I see that no contribution made for openNLP forum, where as coreNLP forum is still going active. So I wanted to understand if stanford:coreNLP has become more popular and been widely used in commercial applications? Anyone has an idea about it?

Answer 1

Apache OpenNLP is actively developed. Take a look at the commit history [1], there are commits done almost everyday by different contributors and they cut four releases this years (1.7.0, 1.7.1, 1.7.2, and just recently 1.8.0).

OpenNLP is licensed under company friendly Apache License 2.0, compared to CoreNLP which is licensed under GPL which is difficult to use in commercial software (e.g. software being distributed must be released under GPL as well), but they are selling commercial licenses.

OpenNLP is developed mostly by companies which run it in their production systems, where CoreNLP is made by a researchers at Stanford.

CoreNLP has a quite a few dependencies which are pulled into your project, where OpenNLP has zero dependencies.

OpenNLP can support you with the following tasks:

• Sentence Detection
• Tokenization
• Chunking
• Named Entity Recognition
• Pos Tagging
• Parsing
• Stemming
• Language Model
• Lemmatization
• Document classification

OpenNLP is highly customizable, easy to train on user data, has support for training on many publicly available corpora and features built-in evaluation to measure performance of every component.

CoreNLP supports these tasks:

• Sentence Detection
• Tokenization
• Named Entity Recognition
• Pos Tagging
• Parsing (also dependency parsing)
• Sentiment
• Coreference
• Lemmatization
• Relation Extraction

[1] https://github.com/apache/opennlp/commits/master