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--- |
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language: |
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- gl |
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- es |
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license: cc-by-4.0 |
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--- |
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# Dataset Card for Spanish–Galician Legal Corpus |
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## Dataset Summary |
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This dataset is derived from the **Translation Memory of the Directorate-General for Translation [(DGT-TM)](https://joint-research-centre.ec.europa.eu/language-technology-resources/dgt-translation-memory_en), a massive multilingual resource created by the European Commission. |
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The original corpus contains the *Acquis Communautaire* (EU legislation) aligned across 24 official languages. |
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The result is a **parallel corpus in Spanish–Galician**, focused on legal texts, with approximately **320,000 aligned sentence pairs**. |
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While Galician is not included in the original release, Portuguese is. Using automatic transliteration and translation techniques, Portuguese segments were adapted into Galician. |
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This adaptaion leveraged transliteration and localization tools found in our text [pipeline](https://github.com/proxectonos/pipeline) and [Apertium](https://github.com/apertium). |
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The resulting texts were then normalized, ensuring linguistic consistency and readiness for model development. |
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## Dataset Creation |
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- **Apertium pt-gl**: We translate original Portuguese segments into Galician using symbolic rules. |
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- **Transliteration and localization**: Using [port2gal](https://github.com/gamallo/port2gal), we improve Apertium's output by processing all leftover tags for out-of-vocabulary words, which we either transliterate to Spanish orthography or localize to a more common Galician word. |
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- **Encoding errors**: The entire text was scanned for encoding errors ensuring it is utf-8 encoded. |
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- **Deduplication**: The filtered datasets were deduplicated to remove redundant sentence pairs. |
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- **Pyplexity**: We used [pyplexity](https://github.com/citiususc/pyplexity) to filter texts that may contain non-linguistic content. |
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- **Normalization**: The final Galician text present here was normalized (linguistically) to adhere to the autonomous standard of the Galician language. |
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## Supported Tasks and Benchmarks |
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- **Machine Translation (MT):** Training and evaluation of MT systems for Spanish ↔ Galician. |
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- **Bilingual Lexicon Induction:** Building dictionaries and glossaries for under-resourced language pairs. |
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- **Evaluation:** Benchmarking translation quality in legal-domain corpora. |
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- **Cross-lingual NLP:** Supporting tasks such as multilingual embeddings and semantic alignment. |
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## Languages |
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- Spanish-Galician |
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## Dataset Structure |
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- **Format:** Parallel text segments (aligned sentences) |
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- **Domain:** Legal texts (EU legislation) |
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- **Size:** ~320,000 lines |
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## Use Cases |
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- Training MT models for Galician, a low-resource language. |
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- Creating bilingual dictionaries and glossaries. |
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- Evaluating translation systems in specialized legal domains. |
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- Supporting research in cross-lingual transfer and underrepresented languages. |
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## Limitations |
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- Domain-specific: Primarily legal texts, which may not generalize to everyday language. |
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- Automatically adapted Galician segments may contain transliteration or translation artifacts. |
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## Funding |
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This work is funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the project Desarrollo de Modelos ALIA. |
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Esta publicación del proyecto Desarrollo de Modelos ALIA está financiada por el Ministerio para la Transformación Digital y de la Función Pública y por el Plan de Recuperación, Transformación y Resiliencia – Financiado por la Unión Europea – NextGenerationEU. |
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