NLP-Cube

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NLP-Cube is an Open Source & Models tool that provides a natural language processing pipeline. It supports sentence splitting, tokenization, lemmatization, part-of-speech tagging, and dependency parsing for multiple languages.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is NLP-Cube?

NLP-Cube is an open-source Natural Language Processing Framework designed to perform various NLP tasks such as sentence segmentation, tokenization, POS tagging (both language-independent UPOSes and language-dependent XPOSes/ATTRs), lemmatization, and dependency parsing. It supports languages included in the UD Treebanks and offers models trained on the UD2.2 corpus, with newer versions using UD 2.7. The framework is built entirely on recurrent neural networks and is written in Python, making it a ready-to-use system for developers and researchers. It provides a simple API for programmatic use and allows for specifying different model versions and 'flavours' to optimize performance for specific use cases. NLP-Cube is freely available on GitHub and can be easily installed via pip.

Best used for

Ideal for developers and data scientists who need to perform end-to-end raw text processing, including sentence splitting, tokenization, and dependency parsing. Especially valuable for researchers and practitioners working with multilingual data and requiring a robust, open-source NLP framework.

Common actions

process natural language

analyze text data

perform linguistic annotation

build NLP applications

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Capabilities

Key features

Sentence segmentation
Tokenization
Lemmatization
Part-of-speech tagging
Dependency parsing
Multilingual support
Python API

Target Audience

developerdata scientiststudentprofessor

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What NLP tasks can NLP-Cube perform?

NLP-Cube is a comprehensive framework that can perform sentence segmentation, tokenization, lemmatization, part-of-speech tagging (UPOSes, XPOSes, ATTRs), and dependency parsing. It provides a full pipeline for processing raw text into structured linguistic annotations.

Which languages does NLP-Cube support?

NLP-Cube supports languages included in the Universal Dependencies (UD) Treebanks. This includes languages like English, Chinese, French, German, Hungarian, Italian, Romanian, and Spanish, with models trained on UD 2.2 and UD 2.7 corpora.

How can I install and use NLP-Cube?

NLP-Cube can be easily installed using pip with the command `pip3 install -U nlpcube`. For programmatic use in Python, you can import the Cube object, initialize it, load the desired language model, and then call it with your text to obtain annotations.

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