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Linguistic Acceptability Assessment/Evidence
Method evidence record

Linguistic Acceptability Assessment

Linguistic acceptability assessment is a natural-language-processing task that automatically estimates whether a sentence would be judged grammatically acceptable by a native speaker of the target language. Grounded in Chomsky's (1957) distinction between grammatical and ungrammatical utterances, the task was formalised as a neural benchmark by Warstadt, Singh and Bowman (2019) through the Corpus of Linguistic Acceptability (CoLA). It is used in language-learning research, linguistics studies, and quality auditing of natural-language-generation (NLG) systems.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Linguistic Acceptability Assessment (Grammaticality Judgment)
Taxonomic method record · process-pipeline / text-mining
  • Warstadt, A., Singh, A. & Bowman, S. (2019). Neural Network Acceptability Judgments. Transactions of the Association for Computational Linguistics, 7, 625–641. · DOI 10.1162/tacl_a_00290
  • Chomsky, N. (1957). Syntactic Structures. Mouton, The Hague. · ISBN 978-9027933249
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyBERT Embeddingsmachine-suggested · Relational suggestion, not evidence.Same method familySentiment Analysismachine-suggested · Relational suggestion, not evidence.Same method familyText Classificationmachine-suggested · Relational suggestion, not evidence.Same method familyTF-IDFmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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