activity
20002021
most citedEnriching very large ontologies using the WWW

255 citations · 490 across the 11 of their papers we have counts for

collaborators

13 papers

cs.CL2021

Impact of detecting clinical trial elements in exploration of COVID-19 literature

Simon Šuster, Karin Verspoor, Timothy Baldwin +4

The COVID-19 pandemic has driven ever-greater demand for tools which enable efficient exploration of biomedical literature. Although semi-structured information resulting from conc…

cs.CL2019

Global Locality in Biomedical Relation and Event Extraction

Elaheh ShafieiBavani, Antonio Jimeno Yepes, Xu Zhong +1

Due to the exponential growth of biomedical literature, event and relation extraction are important tasks in biomedical text mining. Most work only focus on relation extraction, an…

cs.IR2015★ 3 cited

Document Distance for the Automated Expansion of Relevance Judgements for Information Retrieval Evaluation

Diego Mollá, Iman Amini, David Martinez

This paper reports the use of a document distance-based approach to automatically expand the number of available relevance judgements when these are limited and reduced to only pos…

cs.CL2002★ 2 cited

The Basque task: did systems perform in the upperbound?

Eneko Agirre, Elena Garcia, Mikel Lersundi +2

In this paper we describe the Senseval 2 Basque lexical-sample task. The task comprised 40 words (15 nouns, 15 verbs and 10 adjectives) selected from Euskal Hiztegia, the main Basq…

cs.CL2002

Decision Lists for English and Basque

Eneko Agirre, David Martinez

In this paper we describe the systems we developed for the English (lexical and all-words) and Basque tasks. They were all supervised systems based on Yarowsky's Decision Lists. We…

cs.CL2002★ 42 cited

Integrating selectional preferences in WordNet

Eneko Agirre, David Martinez

Selectional preference learning methods have usually focused on word-to-class relations, e.g., a verb selects as its subject a given nominal class. This paper extends previous stat…