Lexical semantics, Basque and Spanish in QTLeapQuality Translation by Deep Language Engineering Approaches

1. Eneko Agirre
2. Iñaki Alegria
3. Nora Aranberri
4. Mikel Artetxe
5. Ander Barrena
6. António Branco
7. Arantza Díaz de Ilarraza
8. Koldo Gojenola
9. Gorka Labaka
10. Arantza Otegi
11. Kepa Sarasola

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More publications in: Procesamiento del lenguaje natural

Abstract

The goal of this FP7 European project is to contribute for the advancement of quality machine translation by pursuing an approach that further relies on semantics, deep parsing and linked open data.

Bibliographic References

• Agerri, R., J. Bermudez, and G. Rigau. 2014. IXA pipeline: Efficient and Ready to Use Multilingual NLP tools. 9th Language Resources and Evaluation Conference (LREC2014), Reykjavik, Iceland. pages 26-36.
• Branco, A. and P. Osenova. 2014. QTLeap - Quality Translation with Deep Language Engineering Approaches. Poster at EAMT2014, Dubrovnik.
• Popel, M. 2014. MT Pilot 1: Entrylevel Deep MT. Internal presentation in QTLeap project Meeting. Lisbon.
• Zeman, D., O. Dusek, D. Marecek, M. Popel, L. Ramasamy, J. Stépánek, Z. Zabokrtský, and J. Hajic. 2014. Hamledt: Harmonized multi-language dependency treebank. Language Resources and Evaluation, 48(4):601-637.

Data source: Dialnet