Root_POS_Identification

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This is the python implementaion of our work here: "A Novel Approach for Root Selection in the Dependency Parsing"

Requirements

Python 3

requirements.txt:
tqdm==4.30.0
scikit-learn==1.0
nltk==3.4.5
torch==1.6.0
pytorch-pretrained-bert==0.4.0
seaborn==0.9.0

Datasets

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AR ArPoT: here
AR CATiB: here
AR PADT | EL GDT | EN EWT | FR ParTUT | TA TTB | TR IMST | ZH GSD : here

Parsing as Sequence labeling

In our work, we have adopted the approach outlined by Vilares et al., utilizing their code as a foundation. Additionally, it is pertinent to acknowledge the contributions of Strzyz et al. for their influential work in the field. Our methodology also aligns with the findings presented in our research article available on MDPI, which further substantiates our approach.

Citation

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@inproceedings{AlGhamdi2024,  
  title={A Novel Approach for Root Selection in the Dependency Parsing},  
  author={Al-Ghamdi, Sharefah and Al-Khalifa, Hend and Al-Salman, Abdulmalik},  
  booktitle={Proceedings of the 6th Workshop on Open-Source Arabic Corpora and Processing Tools},  
  year={2024}  
}

Contact information

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For help or issues send an email to sharefah@ksu.edu.sa.