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README.md
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---
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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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# DaLA: Danish Linguistic Acceptability Evaluation Dataset
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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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## 🔗 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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## 📖 Overview
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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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- 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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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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## 📦 Dataset Variants and Splits
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There are three variants of the DaLA dataset, each with different sizes and proportions:
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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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Each variant includes train, validation, and test splits.
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---
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## 🧠 Tasks & Usage
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DaLA is primarily intended for:
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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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You can load the dataset using the Hugging Face `datasets` library as follows:
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```python
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from datasets import load_dataset
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# Standard split
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dataset = load_dataset("giannor/dala")
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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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## 📊 Baselines & Model Performance
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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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## 📄 Citation
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If you use this dataset in your work, please cite the following paper:
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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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## ⚖️ License
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This dataset is shared under the **CC BY 4.0** license.
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[1]: https://arxiv.org/abs/2512.04799 "DaLA: Danish Linguistic Acceptability Evaluation Guided by Real World Errors"
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