openNLP Reviews & Product Details

I like that it is a useful tool when we have a lot of documents in different languages and we need to detect the language in order to find appropriate translators in order to communicate with members of our community Review collected by and hosted on G2.com.

What I like the most about Apache Open NLP is the language detection because it is very useful when trying to go over papers that are in different languages Review collected by and hosted on G2.com.

We've tried to build production quality NLP applications for a long time, but never gotten anywhere. After switching to openNLP, we had a beta version ready in 3 weeks. It's great to use, easy to implement and the documentation available is amazing Review collected by and hosted on G2.com.

I just wish that openNLP came out with more updated releases faster than their current release cycle. There have definitely been moments where I wished it was more up to date with the current state of the art Review collected by and hosted on G2.com.

openNLP is a great software for companies and businesses that work with multiple languages. Its easy to translate, and dissect words and sentences to easily understand. Review collected by and hosted on G2.com.

OpenNLP is a very useful software that i dont believe has many flaws. This software is very easy to use, and very useful for our business. Review collected by and hosted on G2.com.

Was working on a basic question-answering system using basic NLP methods compared to the Neural Nets. OpenNLP made my process much simpler with its wide variety of functions that are easy to use and when in trouble there is always an easily accessible documentation which is well written to cover almost all the possible general errors. Review collected by and hosted on G2.com.

The NER Tagger and POS tagger are very different when compared to the other packages like spaCy and NLTK, which sometimes makes it harder to compare the outputs over certain categories. Review collected by and hosted on G2.com.

It has really good documentation. Apart from stemming, tokenization and lemmatization there are features like sentence detection, language detection. Review collected by and hosted on G2.com.

It is not yet very widely used so there are very few resources for using it in Python yet. Review collected by and hosted on G2.com.

Supports main NLP tasks such as tokenization and parsing etc. Easy to build something fast and especially easy to install. Documentation is fair. Review collected by and hosted on G2.com.

I would definitely go with Spacy as it is more production focused and some of the tools of OpenNLP are not the most advanced. However, it is not so deep as NLTK and its API is not my favorite. Review collected by and hosted on G2.com.

The truth that everything it promises meets, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, language detection and coreference resolution. Review collected by and hosted on G2.com.

Maybe the part of part-of-speech tagging or chunking and parsing it could be better. Review collected by and hosted on G2.com.

out of the box entity recognition, tokenization, etc is great for projects Review collected by and hosted on G2.com.

not much to dislike to be completely honest Review collected by and hosted on G2.com.

The new language model, Moses format support and unit tests Review collected by and hosted on G2.com.

Concurrency is she poor handling of xml parsers Review collected by and hosted on G2.com.

Advanced Features, Open Source Free Can build a full NLP Pipeline Review collected by and hosted on G2.com.

With any of its features, it produces high accuracy but also at the same time has false negatives. Review collected by and hosted on G2.com.