Awards

Eneko Agirre

Google faculty research awards 2018 (2018)


Olatz Perez de Viñaspre

Euskarazko Tesien VI. Koldo Mitxelena saria (2018)


Aitor Gonzalez

2017 Best Thesis Award at SEPLN (2018)

Aitor Gonzalez Agirre was awarded with the best MSc thesis Award 2018 by the SEPLN association.

Eneko Agirre, Mikel Artetxe, Gorka Labaka, Iñigo López

best paper award of the CoNLL 2018 conference (2018)

Our work "Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation" received the Best Paper Award in CoNLL 2018 conference, in Brussels. Mikel Artetxe, Gorka Labaka, Iñigo Lopez-Gazpio, Eneko Agirre (2018) Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation Proceedings of the 22nd Conference on Computational Natural Language Learning (CoNLL 2018), pages 282–291. Brussels, Belgium, October 31 - November 1, 2018

Aitziber Atutxa, Arantza Casillas, Arantza Díaz de Ilarraza, Nerea Ezeiza, Iakes Goenaga, Koldo Gojenola, Maite Oronoz, Alicia Pérez, Olatz Perez de Viñaspre

Best system at the shared task on Automatic Disability Annotation at Ibereval 2018 (2018)

This work was pursued by the IXAMed group in the DIANN-Ibereval 2018 task. The task consists of identifying disabilities within a collection of several abstracts from Elsevier journal papers related to the biomedical domain. These corpora include the annotation of negation when it applies to a disability. The evaluation of the task is divided in two sub-tasks; one corresponding to the detection of English entities and the other to Spanish entities. Our system achieves the best task F-score for both English and Spanish disability identification, showing the suitability of our approach even with quite small training corpus. Our F-score is 0.821 for English and of 0.786 for Spanish.

Aitziber Atutxa, Arantza Casillas, Arantza Díaz de Ilarraza, Nerea Ezeiza, Iakes Goenaga, Koldo Gojenola, Maite Oronoz, Alicia Pérez, Olatz Perez de Viñaspre, Xabier Soto

Best system for ICD-10 (International Classification of diseases) coding in French, Italian and Hungarian at CLEF eHealth 2018 (2018)

Hospital systems routinely assign disease codes (ICD10 codes) to medical records. The challenge stands on treating natural and non-standard language in which doctors express their diagnoses. We presented our system to the CLEF 2018 eHealth Evaluation Task 1 on Multilingual Information Extraction - ICD10 coding. This benchmark addresses information extraction in written text with focus on several languages, specifically Hungarian, Italian and French. The goal is to automatically assign ICD10 codes to diagnostic terms of death certificates. In total, fourteen teams participated: 14 teams submitted runs for the French dataset, 5 submitted runs for the Hungarian dataset and 6 for the Italian dataset. For death certificate coding, the highest performance was 0.838 F-measure for French, 0.9627 for Hungarian and 0.9524 for Italian.

Mikel Artetxe

Premios Nacionales de Fin de Carrera de Educación Universitaria 2013-2014 (2018)

Premios para estudiantes que hayan concluido sus estudios conducentes a un título universitario oficial de Grado o de Primer o Segundo Ciclo en centros universitarios españoles en el curso 2013-2014

Ixa taldea

Acknowledgment for the contribution made to the Basque community in the area of Information Technology (2018)

Acknowledgment given to the Ixa group by the bascophile association in San Sebastian Bagera (Bagera Donostiako Euskaltzaleen Elkartea) for the contribution made to the Basque community in the area of Information Technology.

Eneko Agirre, Mikel Artetxe, Gorka Labaka

The journal Science made a special mention (2018)

The journal Science made a special mention of the work done by the members of the group Mikel Artetxe, Eneko Agirre and Gorka Labaka in the article entitled Artificial intelligence goes bilingual without a dictionary.