Compare NLTK and openNLP 
At a Glance
Market Segments
Small-Business (52.2% of reviews)
Small-Business (63.6% of reviews)
Entry-Level Pricing
No pricing available
No pricing available
NLTK
Star Rating
(48)4.4 out of 5
Market Segments
Small-Business (52.2% of reviews)
Entry-Level Pricing
No pricing available
Learn more about NLTKopenNLP
Star Rating
(11)4.0 out of 5
Market Segments
Small-Business (63.6% of reviews)
Entry-Level Pricing
No pricing available
Learn more about openNLPSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that openNLP excels in Part of Speech Tagging with a score of 7.4, while NLTK has a slightly lower performance in this area, indicating that openNLP may provide more accurate tagging for various applications.
- Reviewers mention that NLTK shines in Ease of Setup with a score of 9.0, making it more user-friendly for beginners compared to openNLP, which lacks a specific score in this category.
- G2 users highlight that NLTK offers better Quality of Support with a score of 8.2, whereas openNLP's support is rated lower at 7.0, suggesting that users may find more assistance and resources with NLTK.
- Users on G2 report that openNLP has a strong performance in Customizable Models with a score of 7.5, allowing for more tailored solutions, while NLTK's score in this area is not specified, indicating a potential limitation.
- Reviewers mention that NLTK is favored for its Ease of Use with a score of 8.8, which suggests that it may be more intuitive for users compared to openNLP, which has a lower score of 8.3.
- Users say that both products have similar ratings in Named Entity Recognition, with openNLP scoring 7.3, but NLTK's overall performance in related tasks may provide a more comprehensive toolkit for users.
Pricing
Entry-Level Pricing
NLTK
No pricing availableopenNLP
No pricing availableFree Trial
NLTK
No trial information availableopenNLP
No trial information availableRatings
Meets Requirements
7.9
28
8.3
9
Ease of Use
8.8
28
8.3
9
Ease of Setup
9.0
10
Not enough data
Ease of Admin
8.8
10
Not enough data
Quality of Support
8.2
22
7.0
9
Has the product been a good partner in doing business?
9.1
9
Not enough data
Product Direction (% positive)
7.3
26
7.4
9
Features by Category
Algorithm
7.4
23
Not enough data
7.4
19
Not enough data
7.3
22
Not enough data
7.3
22
Not enough data
6.5
20
Not enough data
7.0
21
Not enough data
System
7.6
20
Not enough data
8.0
19
Not enough data
6.4
16
Not enough data
7.2
20
Not enough data
7.5
19
Not enough data
Categories
Categories
Shared Categories
NLTK and openNLP are categorized as Natural Language Understanding (NLU)
Unique Categories
NLTK has no unique categories
openNLP has no unique categories
Reviews
Reviewers' Company Size
NLTK
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
openNLP
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
28.3%
Computer Software
17.4%
Telecommunications
4.3%
Research
4.3%
Internet
4.3%
Other
41.3%
Higher Education
18.2%
Computer Software
18.2%
Warehousing
9.1%
Venture Capital & Private Equity
9.1%
Printing
9.1%
Other
36.4%
Most Helpful Reviews
NLTK
Most Helpful Favorable Review
Harshit P.
Verified User in Information Technology and Services
NLTK includes lot of features for which earlier I was using different library for each feature like tokenization etc.
Most Helpful Critical Review
openNLP
Most Helpful Favorable Review
Mariana S.
Verified User in Higher Education
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
Most Helpful Critical Review
Verified User in Printing
Maybe the part of part-of-speech tagging or chunking and parsing it could be better.
Harshit P.
Verified User in Information Technology and Services
NLTK includes lot of features for which earlier I was using different library for each feature like tokenization etc.
Mariana S.
Verified User in Higher Education
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
Verified User in Printing
Maybe the part of part-of-speech tagging or chunking and parsing it could be better.
Alternatives
Discussions
NLTK has no discussions with answers
openNLP has no discussions with answers
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