--- title: NLTK Reviews meta_title: 'NLTK Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 48 reviews by the users' company size, role or industry to find out how NLTK works for a business like yours. aggregate_rating: rating_value: 4.4 review_count: 48 scale: '5' date_modified: '2026-08-09' parent_category: name: Natural Language Processing (NLP) url: https://www.g2.com/categories/natural-language-processing-nlp --- # NLTK Reviews **Vendor:** NLTK Project **Category:** [Natural Language Understanding (NLU) Software](https://www.g2.com/categories/natural-language-understanding-nlu) **Average Rating:** 4.4/5.0 **Total Reviews:** 48 ## About NLTK NLTK is a platform for building Python programs to work with human language data that provides interfaces to corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. ## NLTK Reviews ### 1. NLTK - A useful toolkit to start with NLP **Rating:** 4.0/5.0 stars **Reviewed by:** Deepanshu D. | Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** May 20, 2022 **What do you like best about NLTK?** I've been working with Python for a long time, and this toolkit has made things a lot simpler. The features contained in the libraries are simple to use and make working with Python more fluid and painless. **What do you dislike about NLTK?** I believe it still lacks a number of functionalities that other competitors have included compared to NLTK. They need to upgrade themselves quickly or they might get left behind in the race. **What problems is NLTK solving and how is that benefiting you?** It has added more support for NLP and made it more powerful by integrating third-party libraries. The main issue it has fixed for me is text processing. ### 2. I have used NLTK extensively to ace Machine Learning Hackathons **Rating:** 4.0/5.0 stars **Reviewed by:** Pratik N. | Technical Writer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 01, 2020 **What do you like best about NLTK?** NLTK has plethora of tools to clean and pre-process your text data. I cannot imagine how many hours it would take to sit and manually clean the text data if it wasn't the amazing in-built of NLTK. I would say NLTK has made life of Data Scientists easy. **What do you dislike about NLTK?** Some of the functionalities like Lemmatization is pretty slow when corpus size is large. So, I have to adjust with stemming. Also, spelling correction functionality doesn't perform that well for SMS language. It would be amazing if the support is extended to identify the words in their short-form. **Recommendations to others considering NLTK:** NLTK is a great tool for Natural Language Processing tasks. The documentation provided is easy to understand with ample of examples. I would certainly recommend it to the beginners who are starting with their Machine Learning journey, as well as the experienced folks in ML industry. **What problems is NLTK solving and how is that benefiting you?** I have used this library primarily for text cleaning in the pre-processing stage and feature extraction before building ML model. While working on Hackathon problems, I tend to experiment with various functionalities of NLTK toolkit for effective processing of the text data. The best part is most of these tools offered by NLTK is quiet easy to implement, mostly can be achieved with a single line of code. Whenever I am stuck, I refer the official NLTK website and public forums and I always able to find the workaround. ### 3. Natural Language ToolKit **Rating:** 4.0/5.0 stars **Reviewed by:** Harshit A. | DevOps Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** July 05, 2022 **What do you like best about NLTK?** Natural Language Processing with Python provides a practical implementation to programming for language processing and we can use with datascience and ml platform for its advance uses **What do you dislike about NLTK?** If your algo is not best then it will impact nltk process. **What problems is NLTK solving and how is that benefiting you?** Its solving out language proceaaing problem that we have faced before python comes in phase. ### 4. NLTK: the go to for Natural Language Processing in python **Rating:** 4.0/5.0 stars **Reviewed by:** Claudio M. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** November 24, 2020 **What do you like best about NLTK?** I really like the overall NLTK's API. I often use the whole pre processing pipeline related API's , I also use TextCat for language identification. I also like the pos-tagging API's and the sentiment analysis one . **What do you dislike about NLTK?** It would be awesome if API's were a little bit faster since by reading some stack overflow answers, I sometimes found users replying to questions presenting some speed benchmarks comparing NLTK's speed with other NLP related libraries and showing it didn't was the fastest one among them . **Recommendations to others considering NLTK:** I recommend the use of NTLK everytime you have to deal with text and you have to perform every type of natural language processing related analysis. It offers easy APIs to deal with every language. You can leverage wordnet api's to calculate synsets distances and related measures. It supports also part of speech tagging , machine translation , dependency parsing and sentiment analysis API's. You can also use neural networks for some specific tasks . **What problems is NLTK solving and how is that benefiting you?** I'm dealing with general natural language processing tasks , such as text mining , text classification and topic modeling. I used nltk textcat to identify and split my data according to detected languages . Then the whole pre processing pipeline was implemented in NLTK. I used wordnet api in order to instantiate a wordnet lemmatizer and used it in conjuction with the pos tag api in order to use lemmatization enriched by pos tagging . ### 5. Nltk: A library for text processing in python **Rating:** 4.0/5.0 stars **Reviewed by:** Alvaro R. | Profesor titular, Enterprise (> 1000 emp.) **Reviewed Date:** October 13, 2020 **What do you like best about NLTK?** Nltk offers differents types of analysis as lemmatization, pos tagging, stop words removal, etc **What do you dislike about NLTK?** The kind of processing may differ depending on the language. Besides, the coverage of applications for each language is different. **Recommendations to others considering NLTK:** Before using nltk, you should check if all the functionalities required for you are available for your language. The language with most applications is English, so you need to know if you can apply similar processing in your language. On the other hand, the way of calling to some functionalities depends on the language because some models are more effective for some language than for another. I also recommend checking the performance of the functionality you want to use. That is, as it is already known in natural language processing, the precision in some tasks is close to 100, while in others it is lower. **What problems is NLTK solving and how is that benefiting you?** I have used nltk to apply previous processing to input texts. For example, nltk helps me to remove stop words, in any language, as well as obtaining lemmans and stems from every word. Besides, I can used also ntlk for name entity recognition in several languages. Thus, I can obtain several features from a single text. One of the main benefits of using nltk is the fact that the processing is quite fast. Moreover, I like the fact that I can find lots of information on the Internet, with several examples. This helps me a lot when I want to process texts using nltk. ### 6. NLTK is very handy for NLP pipelines ! **Rating:** 4.0/5.0 stars **Reviewed by:** M C. | Business Analyst, Enterprise (> 1000 emp.) **Reviewed Date:** December 28, 2020 **What do you like best about NLTK?** The best thing about NLTK is its ease of implementation. Without it to write algorithms from scratch it take ages but it helps in quick prototyping. Another thing that is great about NLTK is it has great pre trained models and corpus of data which makes text processing and analysis pretty quick and easy. **What do you dislike about NLTK?** There is not much to dislike about NLTK but ya it has improved a lot in time. I would like it to more fine tune its algorithms as some of its competitor like SpaCy is doing. It only works syntactically and i would prefer if in future looks into semantic aspect of text as well. Another thing it misses are the neural network models as it has no deep learning capabilities. **Recommendations to others considering NLTK:** Yes I would totally recommend NLTK for others want to get into natural language processing as it is fairly easy to setup and learn. **What problems is NLTK solving and how is that benefiting you?** The main benefit I have realized is quick prototyping with help of NLTK. It helps me to give actual shape to my projects in no time. Another benefit for NLTK is it is very easy and quick to learn so that I can bring my whole team in same page very fast and that really helps in quick research and development. ### 7. Good Start for NLP Techniques **Rating:** 4.0/5.0 stars **Reviewed by:** Ridhima g. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** November 27, 2020 **What do you like best about NLTK?** It is the best package for processing and understanding the text in less coding. It provides so many functionalities such as tokenization, chunking, chinking in text processing, dependency parsing in understanding the text. Documentation is easily available and fully open source. **What do you dislike about NLTK?** You have to download the desired collection such as you want to use wordnet then before using downloading is necessary. **Recommendations to others considering NLTK:** Spacy is also one of the good packages for processing and performing NLP task **What problems is NLTK solving and how is that benefiting you?** I used NLTK majorly for pre-processing in Natural Language Processing tasks such as review classification then each review is in the raw form. Hence we have to perform processing and make it a useful vector. Perfect library for basic processing on the text like stop-word removal, tokenization, etc. ### 8. Great experience with NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Marcelo Q. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** December 03, 2020 **What do you like best about NLTK?** NLTK is easy to use and pretty effective. It also has good documentation and a lot of people using stack overflow to ask and answer questions about it - for a dev, is always important. **What do you dislike about NLTK?** I have no major things I don't dislike but It will be good to add more higher level functions, allowing devs to do more with less code. **Recommendations to others considering NLTK:** It is easy to search text analysis solutions using NLTK. **What problems is NLTK solving and how is that benefiting you?** Predictive projects, mostly, where I had also text analysis to do. One of the projects I can mentione is a financial analysis in the 10-K reports of the major companies in the US. I extracted text complexity indicatores and correlated it with profit. ### 9. NLTK is good tool for college students to learn basics **Rating:** 3.5/5.0 stars **Reviewed by:** Shahid H. | Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** November 26, 2020 **What do you like best about NLTK?** NLTK is easy to learn at the start. It is widely accepted in colleges and universities to teach new students the basics of NLP. NLTK offers basics of NLP and also you can integrate with gensim models for language modeling which I think is upside of NLTK. Researchers use NLTK because it offers basics of NLP. Sentence parser is fast but sometime breaks at wrong position. **What do you dislike about NLTK?** NLTK doesn't offer some things that its competitors do. For example word parser of NLTK is slow as compared to spacy. Spacy returns object which can easily used in further operations while NLTK returns string. POS tagging is very slow and same for NER. In industry, Spacy is widely used. **Recommendations to others considering NLTK:** New researcher in NLP and new students can use NLTK to learn the basics of NLP. I would recommend using Gensim and wordnet with NLTK. It would enhance your experience. **What problems is NLTK solving and how is that benefiting you?** I have used it in start of my career and in university to learn basics. I have used it for word/sentence similarity using gensim models. ### 10. Junior Data Scientist **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 06, 2020 **What do you like best about NLTK?** I find NLTL less complicated as most of the pre processing required for the text data are readily available that can be used directly without any modification required. It does include all the basic functions required to clean the data when working with AI **What do you dislike about NLTK?** I would not put it as dislike but as and when more things like spacy have come up NLTK scores little down . For all the basic computations its an ease may be little slow when compared to other libraries and quite not accurately updated with the flow AI is moving **Recommendations to others considering NLTK:** YEs I would definitely recommend beginners to use NLTK ,this is the first thing that pops up when working on a NLP project. Its like a go to library to start with a project .due to its simplicity I would always like to try with NLTK and only if something dose not work with this then I would prefer or research about other libraries **What problems is NLTK solving and how is that benefiting you?** Sometimes gets slow while downloading the functions , and things like categorizing the data is not well done . Benefit is the simplicity in the usage ### 11. Senior Machine Learning Engineer with 4+ years of experience **Rating:** 4.0/5.0 stars **Reviewed by:** Uridah S. | Senior Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 01, 2020 **What do you like best about NLTK?** I work mostly in python. I know it is available for a number of languages but I will review only for python. It provides a variety of features from tokenization to stemming and lemmatization. Having these basic features allow you to get basic NLP tasks without having to do anything complicated. Another pro of NLTK is that it is really easy to use and you can get started right away. **What do you dislike about NLTK?** It doesn't provide any advanced features and lack of neural networks affect its performance where sometimes it makes mistake when lemmatizing and stemming very basic words. **What problems is NLTK solving and how is that benefiting you?** I always use NLTK in combination with other libraries. ### 12. Review of NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Hassan J. | Sr Machine Learning Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 10, 2020 **What do you like best about NLTK?** Over all NLTK serves quite well for my use case. It helps with NLP pipelines. NLTK has a very good stop words corpus as well. I have also used NLTK for intent detection and the results were quite satisfactory given the small dataset we used **What do you dislike about NLTK?** NLTK is kinda slow. There should performance improvement both when it comes to time and memory usage. Also with introduction of more advance language models, maybe NLTk should also incorporate some more deep nueral network models **What problems is NLTK solving and how is that benefiting you?** Using NLTK for Stop Words For Intent Detection Also used in combination with Spacy for NER ### 13. powerfull tool for text analysis **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Mid-Market (51-1000 emp.) **Reviewed Date:** November 29, 2020 **What do you like best about NLTK?** With NLTK was super useful in carrying out a sentiment analysis on movie reviews, furthermore, the corpora present in NLTK are useful in carrying out comparisons for text analysis. Features that I found extremely useful are all the helping function present for tokenization of the text. **What do you dislike about NLTK?** It would be nice to automatically generate graphs since for word distribution there is a little tinkering to do to make the graph look good. But overall not much to complain about. **What problems is NLTK solving and how is that benefiting you?** Text analysis and sentiment analysis. Great overview of the text with easy steps. ### 14. Wonderful tool for NLP **Rating:** 4.0/5.0 stars **Reviewed by:** Ali R. | Software Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 28, 2021 **What do you like best about NLTK?** It is easy as described in documentation and very dominant tool when it comes to text cleaning and processing. **What do you dislike about NLTK?** I do not think, there is anything to be dislike. **Recommendations to others considering NLTK:** Recommended for Natural Language Processing task. **What problems is NLTK solving and how is that benefiting you?** The problems i used to solve with NLTK is text processing. It helps me a lot. ### 15. Had a wonderful experience with NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Shaheer R. | Software Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 30, 2020 **What do you like best about NLTK?** It is very handy to understand and for searching and analysis with easy documentation. **What do you dislike about NLTK?** Nothing to dislike but it contains only basic functionalities but hope it includes much more in the future. **What problems is NLTK solving and how is that benefiting you?** I frequently used NLTK for the data to embedding conversion and it came out very useful and amazing. I also used it with leaning deep learning libraries with sentiment analysis. ### 16. The grand-old-man of Natural Language Processing **Rating:** 4.0/5.0 stars **Reviewed by:** Siddhant S. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** December 01, 2020 **What do you like best about NLTK?** Easy learning curve, ease of implementation **What do you dislike about NLTK?** Slow compared to newer NLP frameworks like SpaCy and Gensim **What problems is NLTK solving and how is that benefiting you?** Text preprocessing for classification, named entity recognition. Very easy to learn and prototype compared to other frameworks. ### 17. Good book covering most of the important topics **Rating:** 4.0/5.0 stars **Reviewed by:** Mohan K. | Senior Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** August 12, 2020 **What do you like best about NLTK?** All the fundamental topics are covered in this book Topics around nltk also covered extensively Go to book when it comes to any natural language processing related coding for python **What do you dislike about NLTK?** I feel the latest technological advancements are not there in this book something like word embedding glove vectors word2vec vectors are missing. deep learning techniques like rnn lstm are missing **Recommendations to others considering NLTK:** Good **What problems is NLTK solving and how is that benefiting you?** We solve many of the NLP problems like text classification text summarisation, text analysis, unsupervised learning from text, extracting the relevant phrases from the text. Understanding key topics from large amount of text ### 18. Book covering most of the topics related to NLTK **Rating:** 4.0/5.0 stars **Reviewed by:** Shaheer R. | Application Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** All basic topics covered with detailed knowledge and easy to understand. **What do you dislike about NLTK?** I do not think, there is something to be disliked. **What problems is NLTK solving and how is that benefiting you?** We are using for our machine learning program to process text. It really helped a lot. ### 19. Good for knowing general NLP **Rating:** 4.0/5.0 stars **Reviewed by:** Peng (Eric) Y. | Project Manager, Small-Business (50 or fewer emp.) **Reviewed Date:** December 02, 2020 **What do you like best about NLTK?** The structure of the content is quite clear. **What do you dislike about NLTK?** The detailed content is normally too repeating and it may fail you in detail understanding. **What problems is NLTK solving and how is that benefiting you?** Social listening engine, segment analysis, and text understanding. ### 20. extensive work on NLP **Rating:** 3.5/5.0 stars **Reviewed by:** Gangadhar D. | Data Scientist, Mid-Market (51-1000 emp.) **Reviewed Date:** November 30, 2020 **What do you like best about NLTK?** Rich library and easy to handle working examples for better understanding **What do you dislike about NLTK?** mathematical explanations behind examples would be helpful **What problems is NLTK solving and how is that benefiting you?** POS tagging Embedding Semantic understanding ### 21. NLP for Python users **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Leisure, Travel & Tourism | Enterprise (> 1000 emp.) **Reviewed Date:** September 28, 2018 **What do you like best about NLTK?** Great for NLP uses like sentiment analysis and text classification; open source **What do you dislike about NLTK?** There are not a lot of NLP options so I mainly use this one, takes a while to get used to it **What problems is NLTK solving and how is that benefiting you?** Sentiment analysis of text reviews ### 22. Good all around tool. **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Consumer Services | Small-Business (50 or fewer emp.) **Reviewed Date:** December 14, 2017 **What do you like best about NLTK?** NLTK makes it easy for me to create grammar rules in order to find specific structures in my text data. The parsers, corpuses, and taggers that it provide are essential in my ML pipeline. **What do you dislike about NLTK?** Sometimes creating the rules that you want can be a pain, but that's just part of learning the tool. **What problems is NLTK solving and how is that benefiting you?** I'm using NLTK to help preprocess text data in our machine learning pipelines. It has helped to speed up our process tremendously. ## NLTK Discussions - [What is NLTK used for?](https://www.g2.com/discussions/what-is-nltk-used-for) - [View NLTK pricing details and edition comparison](https://www.g2.com/products/nltk/reviews?filters%5Bnps_score%5D%5B%5D=4§ion=pricing&secure%5Bexpires_at%5D=2026-08-13+14%3A28%3A07+-0500&secure%5Bsession_id%5D=d496ead3-27d8-4acb-ace4-e5d125239727&secure%5Btoken%5D=322a5b170d473b880cbf81575f80edb8be1726d248a2f5044e363b4ff5ebc87e&format=llm_user) ## NLTK Features **Additional Functionality** - Tagging - Natural Language Processing - Data Extraction - Multi-Language - Predictive Analytics - Drag & Drop - Speech Recognition - Reporting/Analytics - Data Storage Management - Virtual Personal Assistant (VPA) - AI Copilot - Customer Segmentation - Collaboration Tools - Data Import/Export - Generative AI - For eCommerce - Role-Based Permissions - Customizable Branding - Search/Filter - Monitoring - Document Management - API - Data Visualization - Trend Analysis - Machine Learning - Access Controls/Permissions - Alerts/Escalation - Performance Metrics - Real-Time Data - Third-Party Integrations - Mobile App - Multiple Data Sources - For Sales Teams/Organizations - Sentiment Analysis - Activity Dashboard - Chatbot - Workflow Automation **Algorithm** - Part of Speech Tagging - Summarization - Named Entity Recognition - Sentiment Analysis - Emotion Detection - Language Detection **System** - Data Ingestion & Wrangling - Programming Language Support - Drag and Drop - Pre-Built Algorithms - Customizable Models ## Top NLTK Alternatives - [openNLP](https://www.g2.com/products/opennlp/reviews) - 4.0/5.0 (11 reviews) - [Stanford CoreNLP](https://www.g2.com/products/stanford-corenlp/reviews) - 4.3/5.0 (10 reviews) - [Amazon Comprehend](https://www.g2.com/products/amazon-comprehend/reviews) - 4.3/5.0 (83 reviews)