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Document level Attitude and Relation Extraction toolkit (AREkit) for sampling and prompting mass-media news into datasets for ML-model training
AREkit (Attitude and Relation Extraction Toolkit) -- is a python toolkit, devoted to document level Attitude and Relation Extraction between text objects from mass-media news.
This toolkit aims at memory-effective data processing in Relation Extraction (RE) related tasks.
Figure: AREkit pipelines design. More on ARElight: Context Sampling of Large Texts for Deep Learning Relation Extraction paper
In particular, this framework serves the following features:
terms
or sentences
),The core functionality includes:
pip install git+https://github.com/nicolay-r/AREkit.git@0.25.1-rc
Please follow the tutorial section on project Wiki for mode details.
A great research is also accompanied by the faithful reference. if you use or extend our work, please cite as follows:
@inproceedings{rusnachenko2024arelight,
title={ARElight: Context Sampling of Large Texts for Deep Learning Relation Extraction},
author={Rusnachenko, Nicolay and Liang, Huizhi and Kolomeets, Maxim and Shi, Lei},
booktitle={European Conference on Information Retrieval},
year={2024},
organization={Springer}
}
FAQs
Document level Attitude and Relation Extraction toolkit (AREkit) for sampling and prompting mass-media news into datasets for ML-model training
We found that arekit demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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