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A suite of Arabic natural language processing tools developed by the CAMeL Lab at New York University Abu Dhabi.
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CAMeL Tools is suite of Arabic natural language processing tools developed bytheCAMeL LabatNew York University Abu Dhabi.
Please useGitHub Issuesto report a bug or if you need help using CAMeL Tools.
You will need Python 3.8 - 3.12 (64-bit) as well asthe Rust compiler installed.
You will need to install some additional dependencies on Linux and macOS.Primarily CMake, and Boost.
On Ubuntu/Debian you can install these dependencies by running:
sudo apt-get install cmake libboost-all-dev
On macOS you can install them using Homewbrew by running:
brew install cmake boost
pip install camel-tools# or run the following if you already have camel_tools installedpip install camel-tools --upgradeOn Apple silicon Macs you may have to run the following instead:
CMAKE_OSX_ARCHITECTURES=arm64 pip install camel-tools# or run the following if you already have camel_tools installedCMAKE_OSX_ARCHITECTURES=arm64 pip install camel-tools --upgrade# Clone the repogit clone https://github.com/CAMeL-Lab/camel_tools.gitcd camel_tools# Install from sourcepip install.# or run the following if you already have camel_tools installedpip install --upgrade.
To install the datasets required by CAMeL Tools components run one of thefollowing:
# To install all datasetscamel_data -i all# or just the datasets for morphology and MLE disambiguation onlycamel_data -i light# or just the default datasets for each componentcamel_data -i defaults
SeeAvailable Packagesfor a list of all available datasets.
By default, data is stored in~/.camel_tools.Alternatively, if you would like to install the data in a different location,you need to set theCAMELTOOLS_DATA environment variable to the desiredpath.
Add the following to your.bashrc,.zshrc,.profile,etc:
export CAMELTOOLS_DATA=/path/to/camel_tools_dataNote: CAMeL Tools has been tested on Windows 10. The Dialect Identificationcomponent is not available on Windows at this time.
pip install camel-tools -f https://download.pytorch.org/whl/torch_stable.html# or run the following if you already have camel_tools installedpip install --upgrade -f https://download.pytorch.org/whl/torch_stable.html camel-tools# Clone the repogit clone https://github.com/CAMeL-Lab/camel_tools.gitcd camel_tools# Install from sourcepip install -f https://download.pytorch.org/whl/torch_stable.html.pip install --upgrade -f https://download.pytorch.org/whl/torch_stable.html.
To install the data packages required by CAMeL Tools components, run one of thefollowing commands:
# To install all datasetscamel_data -i all# or just the datasets for morphology and MLE disambiguation onlycamel_data -i light# or just the default datasets for each componentcamel_data -i defaults
SeeAvailable Packagesfor a list of all available datasets.
By default, data is stored inC:\Users\your_user_name\AppData\Roaming\camel_tools.Alternatively, if you would like to install the data in a different location,you need to set theCAMELTOOLS_DATA environment variable to the desiredpath. Below are the instructions to do so (on Windows 10):
- Press theWindows button and type
env. - Click onEdit the system environment variables (Control panel).
- Click on theEnvironment Variables... button.
- Click on theNew... button under theUser variables panel.
- Type
CAMELTOOLS_DATAin theVariable name input box and thedesired data path inVariable value. Alternatively, you can browse for thedata directory by clicking on theBrowse Directory... button. - ClickOK on all the opened windows.
To get started, you can follow alongthe Guided Tourfor a quick overview of the components provided by CAMeL Tools.
You can find thefull online documentation here for boththe command-line tools and the Python API.
Alternatively, you can build your own local copy of the documentation asfollows:
# Install dependenciespip install sphinx myst-parser sphinx-rtd-theme# Go to docs subdirectorycd docs# Build HTML docsmake html
This should compile all the HTML documentation in todocs/build/html.
If you find CAMeL Tools useful in your research, please citeour paper:
@inproceedings{obeid-etal-2020-camel,title ="{CAM}e{L} Tools: An Open Source Python Toolkit for {A}rabic Natural Language Processing",author ="Obeid, Ossama and Zalmout, Nasser and Khalifa, Salam and Taji, Dima and Oudah, Mai and Alhafni, Bashar and Inoue, Go and Eryani, Fadhl and Erdmann, Alexander and Habash, Nizar",booktitle ="Proceedings of the 12th Language Resources and Evaluation Conference",month = may,year ="2020",address ="Marseille, France",publisher ="European Language Resources Association",url ="https://www.aclweb.org/anthology/2020.lrec-1.868",pages ="7022--7032",abstract ="We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python. CAMeL Tools currently provides utilities for pre-processing, morphological modeling, Dialect Identification, Named Entity Recognition and Sentiment Analysis. In this paper, we describe the design of CAMeL Tools and the functionalities it provides.",language ="English",ISBN ="979-10-95546-34-4",}
CAMeL Tools is available under the MIT license.See theLICENSE filefor more info.
If you would like to contribute to CAMeL Tools, please read theCONTRIBUTE.rstfile.
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A suite of Arabic natural language processing tools developed by the CAMeL Lab at New York University Abu Dhabi.
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