openNLP Reviews & Product Details


What is openNLP?

Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text that supports the 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 and includes maximum entropy and perceptron based machine learning.

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openNLP Profile Details

openNLP Profile Details

Vendor
The Apache Software Foundation
Description
Community-led development since 1999. FoundationProjectsPeopleGet InvolvedDownloadSupport ApacheHome. We consider ourselves not simply a group of projects sharing a server, but rather a community of developers and users.
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Year Founded
1999
HQ Location
Wakefield, MA
LinkedIn® Page
www.linkedin.com
Employees on LinkedIn®
1,824
Twitter
@TheASF
Twitter Followers
53,993
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openNLP Reviews

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openNLP Reviews

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Software Developer
Mid-Market
(51-200 employees)
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"Open Source Natural Language Text"

What do you like best?

Apache OpenNLP is an open source Java library which is utilized procedure Natural Language content. OpenNLP gives administrations, for example, tokenization, sentence division, grammatical form labeling, named substance extraction, piecing, parsing, and co-reference goals, and so on. In this instructional exercise, we will see how to utilize the OpenNLP library to manufacture an effective content handling administration.

What do you dislike?

Python has extensive support for NLP like sklearn Bag of Words and Tfidf vectorizer which are far more efficient .

Recommendations to others considering the product:

It is utilized for producing data from a database and robotizing the data reports, for example, climate investigation or restorative reports.

What problems are you solving with the product? What benefits have you realized?

We use it to break down human speech, NLP has some builtin highlights for this necessity.

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Software Engineer
Computer Software
Mid-Market
(201-500 employees)
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"Abandoned before it's prime"

What do you like best?

OpenNLP has a nice and easy to understand API. The library is usable as a stand alone command line tool but can also be used within products which makes it easy to test new ideas on the CLI and the transition to productionizing a prototype is quick.

What do you dislike?

The project has been abandoned and is no longer up to date. There's also no indication in any parts of the API as to which functions and classes are thread safe versus not. I wish there was more example code in the documentation, and the models that have been trained that are available for download are from very long ago.

Recommendations to others considering the product:

The documentation is lack luster. You will be doing a lot of your own digging.

What problems are you solving with the product? What benefits have you realized?

Consistent tokenization and named entity recognition have been useful.

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"Has reduced bar for usable NLP applications"

What do you like best?

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

What do you dislike?

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

Recommendations to others considering the product:

Check out openNLP integrations with other Apache products

What problems are you solving with the product? What benefits have you realized?

We're using openNLP based analysis to parse feedback comments and realize better customer service. After switching to openNLP, the time taken from feedback to action has gone down by a factor or two and our approval ratings have shot up

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UI
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(5001-10,000 employees)
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"Good tool but still needs a lot of improvements"

What do you like best?

OpenNlp is not a very widely used tool, but once you start using it, you really see the advantages it offers over other such products. The inbuilt functions help you to reduce time and effort for Text Parsing, Entity recognition and getting the language patterns.

What do you dislike?

Nothing major to dislike in the latest version as they have brought a lot of improvements and added advanced functionality which was missing in the previous versions. They need to do this on a more regular basis to stay ahead of the competition.

What problems are you solving with the product? What benefits have you realized?

Well, have been able to make quite good progress in the NLP field after we introduced OpenNLP because it has helped us to understand the raw data and patterns in a much more meaningful way in way lesser time. The best part about it is the Documentation, which is written superbly by an excellent technical team behind this tool.

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Spanish Professor
Mid-Market
(51-200 employees)
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"Apache OpenNLP "

What do you like best?

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

What do you dislike?

Whay I like the most about Apache Open NLP is the language detection because it is very useful when trying to fo over papers that are in different languages

What problems are you solving with the product? What benefits have you realized?

We are able to figure out language of different flyers and then we find translators to that language in order to communicate with members of the community.

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Coordinadora de Producción de Vacunas Bacterianas
Small-Business
(11-50 employees)
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Business partner of the vendor or vendor's competitor, not included in G2 scores.

"Excellent Apache Tool"

What do you like best?

apache nlp is an excellent tool with which we can deploy a machine to learn how to use Apache tools. In itself it is a very good library and that allows you to increase your learning with respect to everything about apache

What do you dislike?

while apache remains open source and allows learning and launch of open applications. There will be no complaints from me

Recommendations to others considering the product:

text processing and analysis

What problems are you solving with the product? What benefits have you realized?

at the business level no contribution. It only helps me increase my knowledge

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Warehouse Manager
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"Amazing communication software"

What do you like best?

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.

What do you dislike?

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.

What problems are you solving with the product? What benefits have you realized?

Our company deals with many languages, and this software helps us to bridge language barriers, and to communicae with all of our clients.

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Account Manager
Enterprise
(5001-10,000 employees)
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"OpenNLP as a toolkit."

What do you like best?

It is a machine learning based toolkit for processing of natural language text.

It supports the most common NLP tasks such as language detection,tokenization, sentence segmentation, part-of-speech tagging,named entity extraction,chunking,parsing and coreference resolution.

What do you dislike?

It requires computer Literacy to operate which is not too common among most people.

What problems are you solving with the product? What benefits have you realized?

Processing of natural language text.

I use it for language detection therefore enhancing harmony with my clients.

I use it for coreferencing resolution.

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"Great Open Source Natural Language Processing Library "

What do you like best?

It has really good documentation. Apart from stemming, tokenization and lemmatization there are features like sentence detection, language detection.

What do you dislike?

It is not yet very widely used so there are very few resources for using it in Python yet.

Recommendations to others considering the product:

Try using this toolkit, it has its own advantages over NLTK because it's more like an API.

What problems are you solving with the product? What benefits have you realized?

All the NLP problems are easily solved with much less code node because of openNLP.

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Enterprise
(1001-5000 employees)
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"A good tool for Text ML tasks"

What do you like best?

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.

What do you dislike?

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.

What problems are you solving with the product? What benefits have you realized?

Mainly using it for my research and academic coursework and projects.

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(2-10 employees)
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"Great for NLP"

What do you like best?

Supports main NLP tasks such as tokenization and parsing etc. Easy to build something fast and especially easy to install. Documentation is fair.

What do you dislike?

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.

What problems are you solving with the product? What benefits have you realized?

Text classification

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A
Mid-Market
(501-1000 employees)
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"Good library but not the best"

What do you like best?

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.

What do you dislike?

Maybe the part of part-of-speech tagging or chunking and parsing it could be better.

Recommendations to others considering the product:

Programmers looking for a simple but useful library.

What problems are you solving with the product? What benefits have you realized?

Programing more efficiently.

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"Easy to use"

What do you like best?

Advanced Features,

Open Source

Free

Can build a full NLP Pipeline

What do you dislike?

With any of its features, it produces high accuracy but also at the same time has false negatives.

Recommendations to others considering the product:

It has multiple features and a great ML tool

What problems are you solving with the product? What benefits have you realized?

Used it for Tokenization. POS Tagger

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C
Small-Business
(2-10 employees)
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"openNLP Review"

What do you like best?

out of the box entity recognition, tokenization, etc is great for projects

What do you dislike?

not much to dislike to be completely honest

What problems are you solving with the product? What benefits have you realized?

I was doing text analysis of consumer feedback data

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Enterprise
(10,001+ employees)
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"Great for start ups"

What do you like best?

The new language model, Moses format support and unit tests

What do you dislike?

Concurrency is she poor handling of xml parsers

What problems are you solving with the product? What benefits have you realized?

Assisting with splitting of sentences and using models already provides

openNLP User Ratings

8.3
Ease of Use
Average: 8.6*
7.0
Quality of Support
Average: 8.2*
6.7
Ease of Setup
Average: 8.7*
* Natural Language Processing (NLP) Category
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