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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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- 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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  The result is a **parallel corpus in Spanish–Galician**, focused on legal texts, with approximately **320,000 aligned sentence pairs**.
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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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  - **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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  ## 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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+ ## Dataset Creation
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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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+
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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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  - **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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+
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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)