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README.md

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+---
+license: cc-by-sa-4.0
+language:
+- sv
+tags:
+- readability
+- text-complexity
+- swedish
+- lix
+- linguistics
+- nlp
+task_categories:
+- text-classification
+- text-generation
+pretty_name: Swedish Text Complexity
+size_categories:
+- 1K<n<10K
+---
+
+# Swedish Text Complexity Dataset
+
+A corpus of Swedish texts annotated with readability and linguistic complexity metrics, created by the [Department of Linguistics and Philology at Uppsala University](https://www.uu.se/en/department/linguistics-and-philology).
+
+## Dataset Description
+
+This dataset contains Swedish text passages annotated with multiple complexity metrics, designed to support research in:
+
+- **Controllable text generation** - Train LLMs to generate text at specific reading levels
+- **Educational NLP** - Match texts to student reading proficiency
+- **Text simplification** - Develop automatic simplification systems
+- **Accessibility research** - Create tools for readers with different needs
+- **Readability research** - Study linguistic factors affecting comprehension
+
+## Metrics Included
+
+| Metric | Description | Range |
+|--------|-------------|-------|
+| **LIX** | Läsbarhetsindex (Swedish readability index) | ~20-70+ |
+| **OVIX** | Ordvariationsindex (lexical variation) | Higher = more varied vocabulary |
+| **Nominal Ratio** | Noun/verb density ratio | Higher = more nominal style |
+| **ASL** | Average Sentence Length | words per sentence |
+| **AWL** | Average Word Length | characters per word |
+| **LW%** | Long Word Percentage | % of words >6 characters |
+| **TTR** | Type-Token Ratio | 0-1 (lexical diversity) |
+
+### LIX Score Interpretation
+
+| Score | Category | Typical Examples |
+|-------|----------|------------------|
+| < 25 | Very Easy | Children's books |
+| 25-30 | Easy | Young adult fiction |
+| 30-40 | Medium | Newspapers, popular fiction |
+| 40-50 | Difficult | Official documents, non-fiction |
+| 50-60 | Very Difficult | Academic texts |
+| > 60 | Extremely Difficult | Legal, specialized academic |
+
+## Dataset Structure
+
+```python
+{
+    "id": "wikipedia_sv-a1b2c3d4",
+    "text": "Stockholms tunnelbana öppnades 1950...",
+    "source": "wikipedia_sv",
+    "genre": "encyclopedia",
+    "year": null,
+    "author": "Wikipedia contributors",
+    "license": "CC-BY-SA-4.0",
+    "metrics_num_sentences": 5,
+    "metrics_num_words": 87,
+    "metrics_num_characters": 523,
+    "metrics_num_long_words": 24,
+    "metrics_num_unique_words": 71,
+    "metrics_lix": 42.6,
+    "metrics_lix_category": "difficult",
+    "metrics_ovix": 78.3,
+    "metrics_nominal_ratio": 1.45,
+    "metrics_avg_sentence_length": 17.4,
+    "metrics_avg_word_length": 6.01,
+    "metrics_long_word_pct": 27.6,
+    "metrics_type_token_ratio": 0.816
+}
+```
+
+## Usage
+
+### Loading the Dataset
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("LingFilUU/swedish-text-complexity")
+```
+
+### Filtering by Complexity
+
+```python
+# Get only easy texts (LIX < 30)
+easy_texts = dataset.filter(lambda x: x["metrics_lix"] < 30)
+
+# Get difficult academic-style texts
+difficult = dataset.filter(
+    lambda x: x["metrics_lix"] > 50 and x["metrics_nominal_ratio"] > 1.5
+)
+```
+
+### Training for Controllable Generation
+
+```python
+# Add complexity labels for conditional generation
+def add_complexity_token(example):
+    lix = example["metrics_lix"]
+    if lix < 30:
+        prefix = "<easy>"
+    elif lix < 45:
+        prefix = "<medium>"
+    else:
+        prefix = "<difficult>"
+    example["text_with_prefix"] = f"{prefix} {example['text']}"
+    return example
+
+dataset = dataset.map(add_complexity_token)
+```
+
+## Data Sources
+
+Texts in this dataset are sourced from openly-licensed Swedish corpora:
+
+- **Swedish Wikipedia** (CC-BY-SA-4.0)
+- **Språkbanken resources** (various open licenses)
+- **Project Runeberg** (public domain)
+
+## Methodology
+
+### LIX Calculation
+
+The LIX (Läsbarhetsindex) formula, developed by Carl-Hugo Björnsson (1968):
+
+```
+LIX = (words / sentences) + (long_words × 100 / words)
+```
+
+Where `long_words` = words with more than 6 characters.
+
+### OVIX Calculation
+
+The OVIX (Ordvariationsindex) formula:
+
+```
+OVIX = log(tokens) / log(2 - log(types) / log(tokens))
+```
+
+### Nominal Ratio
+
+Calculated using spaCy's Swedish POS tagger:
+
+```
+NR = (nouns + prepositions + participles) / (verbs + adverbs + pronouns)
+```
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@dataset{lingfiluu_swedish_text_complexity,
+  author = {Department of Linguistics and Philology, Uppsala University},
+  title = {Swedish Text Complexity Dataset},
+  year = {2025},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/datasets/LingFilUU/swedish-text-complexity}
+}
+```
+
+## References
+
+- Björnsson, C.H. (1968). *Läsbarhet*. Stockholm: Liber.
+- Hultman, T.G., & Westman, M. (1977). *Gymnasistsvenska*. Lund: Liber Läromedel.
+- [Språkbanken Text](https://spraakbanken.gu.se/en)
+
+## License
+
+The dataset compilation is released under CC-BY-SA-4.0. Individual texts retain their original licenses as noted in the `license` field.
+
+## Contact
+
+Department of Linguistics and Philology
+Uppsala University
+https://www.uu.se/en/department/linguistics-and-philology