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  ---
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- dataset_info:
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- features:
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- - name: text
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- dtype: string
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- - name: corruption_type
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- dtype: string
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- - name: label
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 150446
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- num_examples: 1024
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- - name: val
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- num_bytes: 34620
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- num_examples: 256
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- - name: test
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- num_bytes: 284960
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- num_examples: 2048
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- - name: full_train
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- num_bytes: 759243
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- num_examples: 5352
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- download_size: 708739
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- dataset_size: 1229269
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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- - split: val
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- path: data/val-*
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- - split: test
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- path: data/test-*
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- - split: full_train
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- path: data/full_train-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language:
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+ - da
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+ pretty_name: DaLA - Danish Linguistic Acceptability Dataset
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+ tags:
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+ - linguistic-acceptability
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+ - nlp
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+ - danish
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+ - benchmark
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+ - text-classification
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+ - minimal-pairs
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+ task_categories:
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+ - text-classification
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+ license: cc-by-4.0
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+ dataset_info:
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+ features:
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+ - name: text
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+ dtype: string
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+ - name: corruption_type
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+ dtype: string
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+ - name: label
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+ dtype: string
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+ splits:
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+ - name: train
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+ num_bytes: 150446
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+ num_examples: 1024
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+ - name: val
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+ num_bytes: 34620
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+ num_examples: 256
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+ - name: test
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+ num_bytes: 284960
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+ num_examples: 2048
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+ - name: full_train
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+ num_bytes: 759243
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+ num_examples: 5352
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+ download_size: 708739
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+ dataset_size: 1229269
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: val
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+ path: data/val-*
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+ - split: test
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+ path: data/test-*
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+ - split: full_train
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+ path: data/full_train-*
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+ size_categories:
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+ - 1K<n<10K
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+ ---
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+
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+
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+ # DaLA: Danish Linguistic Acceptability Evaluation Dataset
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+
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+ **DaLA** ([paper][1]) is a benchmark dataset for **linguistic acceptability judgment** in Danish, designed to evaluate how well NLP models, especially large language models (LLMs), understand grammaticality in real-world Danish sentences. The dataset extends previous resources by introducing a broader and more realistic set of error types and providing data splits suitable for evaluation via few-shot or finetuning.
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+
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  ---
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+
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+ ## 🔗 Links
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+ - DaLA variants are linked and described below
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+ - [Paper][1]
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+ - [GitHub Repository](https://github.com/N-essuno/DaLA) (code, data generation scripts)
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+
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+
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+ ## 📖 Overview
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+
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+ In linguistic acceptability tasks, models must distinguish between **grammatically acceptable** and **unacceptable** sentences. The DaLA dataset was created by:
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+
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+ - Analyzing real-world Danish writing errors.
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+ - Designing **14 distinct corruption functions** that reflect common Danish mistakes (e.g., pronoun confusion, suffix errors, interchange of determiners).
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+ - Applying these corruptions to correct Danish sentences from the Universal Dependencies Danish corpus.
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+ - Pairing each corrupted sentence with its correct counterpart.
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+
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+ The dataset includes:
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+ - The original correct sentences (*acceptable*).
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+ - The corrupted sentences (*unacceptable*).
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+ - A binary acceptability label.
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+ - A corruption type identifier.
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+
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+ ---
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+
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+ ## 📦 Dataset Variants and Splits
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+
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+ There are three variants of the DaLA dataset, each with different sizes and proportions:
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+
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+ | Split Variant | Description | Size (approx.) | Link |
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+ |------------------|-------------|----------------|----------------|
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+ | `dala` | Standard benchmark with proportions comparable to prior Danish acceptability datasets | 3,328 samples | [DaLA Standard](https://huggingface.co/datasets/giannor/dala) |
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+ | `dala_medium` | Expanded version using more available samples | ~6,056 samples | [DaLA Medium](https://huggingface.co/datasets/giannor/dala_medium) |
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+ | `dala_large` | Largest version with the full expanded dataset | ~7,656 samples | [DaLA Large](https://huggingface.co/datasets/giannor/dala_large) |
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+
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+ Each variant includes train, validation, and test splits.
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+
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+ ---
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+
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+ ## 🧠 Tasks & Usage
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+
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+ DaLA is primarily intended for:
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+
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+ ✔ **Model evaluation and benchmarking**: Assessing model competence in grammatical judgment
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+ ✔ **Minimal-pair evaluation**: Error type discrimination and fine-grained analysis
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+
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+ You can load the dataset using the Hugging Face `datasets` library as follows:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Standard split
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+ dataset = load_dataset("giannor/dala")
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+
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+ # Medium or large variants
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+ dataset_medium = load_dataset("giannor/dala_medium")
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+ dataset_large = load_dataset("giannor/dala_large")
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+ ```
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+
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+ ## 📊 Baselines & Model Performance
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+
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+ In the corresponding paper, DaLA was used to benchmark a variety of open-source LLMs and model types. Across many models, performance on DaLA was **lower** than on previous Danish acceptability benchmarks, highlighting DaLA’s **greater difficulty and discriminatory power**. ([DaLA paper][1])
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+
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+ ---
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+
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+ ## 📄 Citation
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+
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+ If you use this dataset in your work, please cite the following paper:
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+
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+ ```bibtex
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+ @misc{barmina2025daladanishlinguisticacceptability,
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+ title={DaLA: Danish Linguistic Acceptability Evaluation Guided by Real World Errors},
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+ author={Gianluca Barmina and Nathalie Carmen Hau Norman and Peter Schneider-Kamp and Lukas Galke},
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+ year={2025},
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+ eprint={2512.04799},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2512.04799},
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+ }
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+ ```
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+
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+ ---
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+
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+ ## ⚖️ License
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+
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+ This dataset is shared under the **CC BY 4.0** license.
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+
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+
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+ [1]: https://arxiv.org/abs/2512.04799 "DaLA: Danish Linguistic Acceptability Evaluation Guided by Real World Errors"