jp-evalb: Robust Alignment-based PARSEVAL Measures

We introduce an evaluation system designed to compute PARSEVAL measures, offering a viable alternative to $\mathtt{\text{evalb}}$ commonly used for constituency parsing evaluation. The widely used $\mathtt{\text{evalb}}$ 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 $\mathtt{\text{jp-evalb}}$, is founded on an alignment method. This method aligns sentences and words when discrepancies arise. It aims to overcome several known issues associated with $\mathtt{\text{evalb}}$ 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.