BLiMP-NL: A Corpus of Dutch Minimal Pairs and Acceptability Judgments for Language Model Evaluation

Abstract We present a corpus of 8,400 Dutch sentence pairs, intended primarily for the grammatical evaluation of language models. Each pair consists of a grammatical sentence and a minimally different ungrammatical sentence. The corpus covers 84 paradigms, classified into 22 syntactic phenomena. Ten sentence pairs of each paradigm were created by hand, while the remaining 90 were generated semi-automatically and manually validated afterwards. Nine of the 10 hand-crafted sentences of each paradigm are rated for acceptability by at least 30 participants each, and for the same 9 sentences reading times are recorded per word, through self-paced reading. Here, we report on the construction of the dataset, the measured acceptability ratings and reading times, as well as the extent to which a variety of language models can be used to predict both the ground-truth grammaticality and human acceptability ratings.

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Publication Details

Journal
Computational Linguistics
Published
2025-01-01
DOI
https://doi.org/10.1162/coli_a_00559
Citations
2
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
4.96

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article

BLiMP-NL: A Corpus of Dutch Minimal Pairs and Acceptability Judgments for Language Model Evaluation

Willem Zuidema, Marianne de Heer Kloots, Michelle Suijkerbuijk, Stefan L. Frank et al.
2 citations
Computational Linguistics
Natural Language Processing Techniques
4.96
article

BLiMP-NL: A Corpus of Dutch Minimal Pairs and Acceptability Judgments for Language Model Evaluation

Willem Zuidema, Marianne de Heer Kloots, Michelle Suijkerbuijk, Stefan L. Frank, Zoë Prins
article en
2 citations

Abstract

Abstract We present a corpus of 8,400 Dutch sentence pairs, intended primarily for the grammatical evaluation of language models. Each pair consists of a grammatical sentence and a minimally different ungrammatical sentence. The corpus covers 84 paradigms, classified into 22 syntactic phenomena. Ten sentence pairs of each paradigm were created by hand, while the remaining 90 were generated semi-automatically and manually validated afterwards. Nine of the 10 hand-crafted sentences of each paradigm are rated for acceptability by at least 30 participants each, and for the same 9 sentences reading times are recorded per word, through self-paced reading. Here, we report on the construction of the dataset, the measured acceptability ratings and reading times, as well as the extent to which a variety of language models can be used to predict both the ground-truth grammaticality and human acceptability ratings.

Computational LinguisticsVol. 51(4)
Radboud University Nijmegen (NL), Stefan University (US), University of Amsterdam (NL), Seijo University (JP)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 6%
Natural Language Processing Techniques
4.96
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