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Apache OpenNLP
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Apache OpenNLP

Overview
Synopsis

The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text.

Category

Text Analytics Software Free

Features

• Named Entity Recognition (NER)
• Document Categorizer
• Sentence Detection
• Parts of Speech Tagging
•Tokenization
•Lemmatization
•Language Detection

License

Open Source

Price

Free

Pricing

Subscription

Free Trial

Available

Users Size

Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)

Company

Apache OpenNLP

What is best?

• Named Entity Recognition (NER)
• Document Categorizer
• Sentence Detection
• Parts of Speech Tagging
•Tokenization

What are the benefits?

• Advanced text processing services.
•. It supports the most common NLP tasks.

PAT Rating™ ( Beta)
Editor Rating
Aggregated User Rating
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Ease of use
7.6
Features & Functionality
7.6
Advanced Features
7.6
Integration
7.6
Performance
7.6
Customer Support
7.6
Implementation
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Bottom Line

Apache OpenNLP is an open-source Java library which is used to process natural language text. You can build an efficient text processing service using this library.

7.6
Editor Rating
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The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. Apache OpenNLP is an open source Java library which is used to process Natural Language text. OpenNLP provides services such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and co-reference resolution, etc. These tasks are usually required to build more advanced text processing services. OpenNLP also included maximum entropy and perceptron based machine learning. The goal of the OpenNLP project will be to create a mature toolkit for the above mentioned tasks. An additional goal is to provide a large number of pre-built models for a variety of languages, as well as the annotated text resources that those models are derived from. The Apache OpenNLP library contains several components, enabling one to build a full natural language processing pipeline. These components include: sentence detector, tokenizer, name finder, document categorizer, part-of-speech tagger, chunker, parser, coreference resolution. Components contain parts which enable one to execute the respective natural language processing task, to train a model and often also to evaluate a model. Each of these facilities is accessible via its application program interface (API). In addition, a command line interface (CLI) is provided for convenience of experiments and training. It is a toolkit, for NLP(Natural Language Processing), based on machine learning and is written in java .

 

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Ease of use
Features & Functionality
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Customer Support
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