jp-evalb: Robust Alignment-based PARSEVAL Measures
<|reference_start|>jp-evalb: Robust Alignment-based PARSEVAL Measures: We introduce an evaluation system designed to compute PARSEVAL measures, offering a viable alternative to \texttt{evalb} commonly used for constituency parsing evaluation. The widely used \texttt{evalb} script has traditionally been employed for evaluating the accuracy of constituency parsing results, albeit with the requirement for consistent tokenization and sentence boundaries. In contrast, our approach, named \texttt{jp-evalb}, is founded on an alignment method. This method aligns sentences and words when discrepancies arise. It aims to overcome several known issues associated with \texttt{evalb} by utilizing the `jointly preprocessed (JP)' alignment-based method. We introduce a more flexible and adaptive framework, ultimately contributing to a more accurate assessment of constituency parsing performance.<|reference_end|>
@article{park2024jp-evalb:,
    title={jp-evalb: Robust Alignment-based PARSEVAL Measures},
    author={Jungyeul Park and Junrui Wang and Eunkyul Leah Jo and Angela Yoonseo
  Park},
    journal={arXiv preprint arXiv:2405.14150},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.14150},
    primaryClass={cs.CL}
}