Mallet VS CoreNLP

Compare Mallet vs CoreNLP and see what are their differences.


MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. (by mimno)
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Mallet CoreNLP
1 4
838 8,225
- 0.4%
7.4 9.7
20 days ago 2 days ago
Java Java
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of Mallet. We have used some of these posts to build our list of alternatives and similar projects.
  • How to get the main topic of a Web article?
    1 project | | 14 Feb 2021
    Nevertheless, you might take a look at the practice of "topic modeling" and get ready for a whole lot of abstruse statistics. One place to start might be Ted Underwoods Topic Modeling Made Just Simple Enough. If you just want to play with some pre-written software that does this kind of thing, you might want to look at MALLET.


Posts with mentions or reviews of CoreNLP. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-27.
  • A comparison of libraries for named entity recognition
    2 projects | | 27 Sep 2021
    If you need NER, there’s no need to implement it yourself. There are several popular libraries that can do this for you nowadays. Five of these libraries, Stanford CoreNLP, NLTK, OpenNLP, SpaCy, and GATE, were already mentioned in the title.
  • Making my own AI assistant
    1 project | | 26 Sep 2021
    Check something like this out to start:
  • Good tutorials for PyTorch?
    1 project | | 26 Aug 2021
    You don't actually even need to learn how to do deep learning if you're doing something fairly basic, which it sounds like you are. There are a lot of good tools you can use basically straight out of the box for something like this. Check out,, and If java's more your thing, add to the list.
  • [D] Java vs Python for Machine learning
    4 projects | | 25 Jul 2021
    To give a contrasting perspective, I think the Java ecosystem is much better suited for many data science tasks, and has a growing and well-maintained set of libraries for general purpose machine learning. I won't list them all, but TF-Java, DJL et al. have implementations of many modern architectures and there are a number of excellent libraries (CoreNLP, Lucene et al.) for working with text.

What are some alternatives?

When comparing Mallet and CoreNLP you can also consider the following projects:

Apache OpenNLP - Mirror of Apache OpenNLP

spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python

DKPro Core - Collection of software components for natural language processing (NLP) based on the Apache UIMA framework.

Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java

CogCompNLP - CogComp's Natural Language Processing libraries and Demos:

Apache Solr - Apache Lucene and Solr open-source search software