Refined Evaluation for End-to-End Grammatical Error Correction Using an Alignment-Based Approach
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AGA5DJDKY" target="_blank" >RIV/00216208:11320/26:GA5DJDKY - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Refined Evaluation for End-to-End Grammatical Error Correction Using an Alignment-Based Approach
Original language description
We propose a refined alignment-based method to assess end-to-end grammatical error correction (GEC) systems, aiming to reproduce and improve results from existing evaluation tools, such as errant, even when applied to raw text input-reflecting real-world language learners' writing scenarios. Our approach addresses challenges arising from sentence boundary detection deviations in text preprocessing, a factor overlooked by current GEC evaluation metrics. We demonstrate its effectiveness by replicating results through a re-implementation of errant, utilizing stanza for error annotation and simulating end-to-end evaluation from raw text. Additionally, we propose a potential multilingual errant, presenting Chinese and Korean GEC results. Previously, Chinese and Korean errant were implemented independently for each language, with different annotation formats. Our approach generates consistent error annotations across languages, establishing a basis for standardized grammatical error annotation and evaluation in multilingual GEC contexts. © 2025 Association for Computational Linguistics.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proc. Main Conf. Int. Conf. Comput. Linguist., COLING
ISBN
979-8-89176-196-4
ISSN
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e-ISSN
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Number of pages
12
Pages from-to
774-785
Publisher name
Association for Computational Linguistics (ACL)
Place of publication
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Event location
Abu Dhabi
Event date
Jan 1, 2026
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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