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README.md
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thus offering a realistic reflection of real-world language errors.
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We randomly selected 1,800 sentences from student essays provided by the bai&by academy, adhering consistently to the ”minimal pairs” criterion. To ensure a balanced diversity, we ensured an
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equal distribution of examples across three proficiency
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Table
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See our paper [*How Well Can BERT Learn the Grammar of an Agglutinative and Flexible-Order Language? The Case of Basque.*]() accepted at LREC-COLING2024 and check our [Github](https://github.com/orai-nlp/bl2mp) for more.
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thus offering a realistic reflection of real-world language errors.
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We randomly selected 1,800 sentences from student essays provided by the bai&by academy, adhering consistently to the ”minimal pairs” criterion. To ensure a balanced diversity, we ensured an
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equal distribution of examples across three proficiency levels (A: Beginner, B: Intermediate, and C: Advanced) and three error types (E1: Declension, E2: Verb, E3: Structure and Order) , as shown in
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the Table below. This approach aimed to represent a vari ety of proficiency levels and error types within the dataset.
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See our paper [*How Well Can BERT Learn the Grammar of an Agglutinative and Flexible-Order Language? The Case of Basque.*]() accepted at LREC-COLING2024 and check our [Github](https://github.com/orai-nlp/bl2mp) for more.
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