jp-evalb: Robust Alignment-based PARSEVAL Measures
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917673623879680 |
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| author | Park, Jungyeul Wang, Junrui Jo, Eunkyul Leah Park, Angela Yoonseo |
| author_facet | Park, Jungyeul Wang, Junrui Jo, Eunkyul Leah Park, Angela Yoonseo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_14150 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | jp-evalb: Robust Alignment-based PARSEVAL Measures Park, Jungyeul Wang, Junrui Jo, Eunkyul Leah Park, Angela Yoonseo Computation and Language 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. |
| title | jp-evalb: Robust Alignment-based PARSEVAL Measures |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2405.14150 |