# jp-evalb: Robust Alignment-based PARSEVAL Measures

arXiv: https://arxiv.org/abs/2405.14150 · HTML: https://mlsanity.com/paper/2405.14150/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 37 references that are in the map.
- First posted on arXiv 23 May 2024.

## Builds on (most cited first, 7 of 7)

- [Grammar as a Foreign Language](https://mlsanity.com/paper/1412.7449/) (2014)
- [Enriched In-Order Linearization for Faster Sequence-to-Sequence Constituent Parsing](https://mlsanity.com/paper/2005.13334/) (2020)
- [Shift-Reduce Constituent Parsing with Neural Lookahead Features](https://mlsanity.com/paper/1612.00567/) (2016)
- [Encoder-Decoder Shift-Reduce Syntactic Parsing](https://mlsanity.com/paper/1706.07905/) (2017)
- [Global Neural CCG Parsing with Optimality Guarantees](https://mlsanity.com/paper/1607.01432/) (2016)
- [A Span-based Linearization for Constituent Trees](https://mlsanity.com/paper/2004.14704/) (2020)
- [End-to-end Graph-based TAG Parsing with Neural Networks](https://mlsanity.com/paper/1804.06610/) (2018)

## Built on by (most cited first, 1 of 1)

- [Non-binary bottom-up constituency parsing without arity actions](https://mlsanity.com/paper/2607.10591/) (2026)

## Abstract (arXiv)

We introduce an evaluation system designed to compute PARSEVAL measures, offering a viable alternative to textttevalb commonly used for constituency parsing evaluation. The widely used textttevalb 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 textttjp-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 textttevalb 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.