Search Results for author: Ander Barrena

Found 10 papers, 5 papers with code

Label Verbalization and Entailment for Effective Zero and Few-Shot Relation Extraction

1 code implementation EMNLP 2021 Oscar Sainz, Oier Lopez de Lacalle, Gorka Labaka, Ander Barrena, Eneko Agirre

In our experiments on TACRED we attain 63% F1 zero-shot, 69% with 16 examples per relation (17% points better than the best supervised system on the same conditions), and only 4 points short to the state-of-the-art (which uses 20 times more training data).

Natural Language Inference Relation +1

EriBERTa: A Bilingual Pre-Trained Language Model for Clinical Natural Language Processing

no code implementations12 Jun 2023 Iker de la Iglesia, Aitziber Atutxa, Koldo Gojenola, Ander Barrena

We demonstrate that EriBERTa outperforms previous Spanish language models in the clinical domain, showcasing its superior capabilities in understanding medical texts and extracting meaningful information.

Language Modelling Transfer Learning

Label Verbalization and Entailment for Effective Zero- and Few-Shot Relation Extraction

1 code implementation8 Sep 2021 Oscar Sainz, Oier Lopez de Lacalle, Gorka Labaka, Ander Barrena, Eneko Agirre

In our experiments on TACRED we attain 63% F1 zero-shot, 69% with 16 examples per relation (17% points better than the best supervised system on the same conditions), and only 4 points short to the state-of-the-art (which uses 20 times more training data).

Natural Language Inference Relation +1

Studying the Wikipedia Hyperlink Graph for Relatedness and Disambiguation

1 code implementation5 Mar 2015 Eneko Agirre, Ander Barrena, Aitor Soroa

Hyperlinks and other relations in Wikipedia are a extraordinary resource which is still not fully understood.

Entity Disambiguation

Matching Cultural Heritage items to Wikipedia

no code implementations LREC 2012 Eneko Agirre, Ander Barrena, Oier Lopez de Lacalle, Aitor Soroa, Fern, Samuel o, Mark Stevenson

Digitised Cultural Heritage (CH) items usually have short descriptions and lack rich contextual information.

Entity Linking

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