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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - text-classification
+  - token-classification
+language:
+  - uk
+tags:
+  - legal
+  - legal-nlp
+  - legislative-quality
+  - definitional-defects
+  - circulus-in-definiendo
+  - ignotum-per-ignotum
+  - ukrainian-law
+size_categories:
+  - 1K<n<10K
+---
+
+# DefectRadar: Definitional Defects in Ukrainian Legislation
+
+Corpus of 5,799 legal definitions extracted from 879 Ukrainian laws (out of 44,021 active legislative acts), annotated for two types of definitional defects:
+
+- **Circulus in definiendo** (tautology): the definition uses the term being defined (or its morphological derivative) in the *differentia specifica*
+- **Ignotum per ignotum** (unknown through unknown): the definition relies on terms that are not defined in the same law
+
+## Key Statistics
+
+| Metric | Value |
+|--------|-------|
+| Legislative acts scanned | 44,021 |
+| Laws with definitions | 879 (2.0%) |
+| Unique definitions | 5,799 |
+| Circulus in definiendo | 1,880 (32.4%) |
+| Cross-reference ignotum | 1,885 (32.5%) |
+| Both defects | 749 (12.9%) |
+| Any defect | 3,016 (52.0%) |
+
+## Error Analysis (LLM-as-Judge Validation)
+
+Pipeline-flagged circulus cases were independently classified by a RAG-augmented GPT-4o judge:
+
+| Classification | % |
+|---------------|---|
+| Domain terminology reuse (morphologically circular but substantively meaningful) | 84.8% |
+| True defect (normatively empty) | 9.1% |
+| False positive | 6.1% |
+
+Ignotum severity stratification:
+
+| Severity | % |
+|----------|---|
+| Cross-reference gap (defined in another law) | 70.8% |
+| Critical (undefined anywhere in corpus) | 20.8% |
+| Common (well-known, no definition needed) | 8.3% |
+
+## Data Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `rada_id` | string | Verkhovna Rada law identifier |
+| `law_title` | string | Official title of the law |
+| `definiendum` | string | The term being defined |
+| `genus_proximum` | string | Superordinate category (genus) |
+| `differentia_specifica` | string | Distinguishing characteristics |
+| `full_definiens` | string | Complete right-hand side of the definition |
+| `is_circulus` | bool | Pipeline circulus detection result |
+| `circulus_tier` | string | Detection tier (morphological / semantic) |
+| `overlapping_lemmas` | list[str] | Lemmas shared between definiendum and differentia |
+| `circulus_explanation` | string | Pipeline explanation |
+| `has_ignotum` | bool | Whether undefined terms were found |
+| `undefined_terms` | list[str] | Terms used but not defined in this law |
+| `ignotum_severity` | string | Severity classification |
+| `ignotum_explanation` | string | Pipeline explanation |
+
+## Source
+
+Definitions extracted from the Verkhovna Rada Open Data portal (`data.rada.gov.ua`) using the LEX AI platform's RadaLegislationAdapter. Corpus snapshot: April 2026.
+
+## Pipeline
+
+The DefectRadar pipeline operates in three stages:
+1. **Definition extraction**: rule-based (em-dash copula patterns) + fine-tuned XLM-RoBERTa for inline definitions
+2. **Circulus detection**: Ukrainian lemmatization (pymorphy2-uk) + genus exclusion + discriminating-adjective overlap
+3. **Ignotum detection**: cross-legislative definition graph across 879 laws
+
+Pipeline code: [github.com/overthelex/secondlayer/tree/main/scripts/defectradar](https://github.com/overthelex/secondlayer/tree/main/scripts/defectradar)
+
+## Citation
+
+```bibtex
+@article{ovcharov2026defectradar,
+  title={DefectRadar: Automated Detection of Definitional Defects in Legislation via Morpho-Semantic NLP Pipeline over 24,000 Ukrainian Laws},
+  author={Ovcharov, Volodymyr and Kyrychenko, Ihor},
+  journal={arXiv preprint},
+  year={2026}
+}
+```
+
+## License
+
+CC BY 4.0