Ixa taldea

Lan honek euskararako korreferentzia-ebazpenean egindako lanari jarraipena ematea du helburu, korreferentzia-ebazpenerako neurona-sareetan oinarritutako sistema bat eraikiz. Horretarako polonierarako eraikitako sistema bat hartu da abiapuntutzat, eta euskarara egokitu. EPEC-KORREF corpusetik abiatuta, aipamen-bikoteak eta hauen ezaugarriak erauzi dira eta neurona-sarea entrenatu da aipamen-bikoteak korreferenteak ote diren erabakitzeko. Jarraian, neurona-sarearen iragarpenetatik korreferentzia-klusterrak sortu eta ebaluatu egin dira.

This paper presents a successful domain adaptation of a general neural machine translation (NMT) system using a bilingual corpus created with captions for images in Wiki- media Commons for the Spanish-Basque and English-Irish pairs. Keywords: Machine Translation, Low-resource languages, Bilingual corpora, Language resources from Wikipedia

Background Automatic extraction of morbid disease or conditions contained in Death Certificates is a critical process, useful for billing, epidemiological studies and comparison across countries. The fact that these clinical documents are written in regular natural language makes the automatic coding process difficult because, often, spontaneous terms diverge strongly from standard reference terminology such as the International Classification of Diseases (ICD). Objective