scispace - formally typeset
G

German Rigau

Researcher at University of the Basque Country

Publications -  176
Citations -  6215

German Rigau is an academic researcher from University of the Basque Country. The author has contributed to research in topics: WordNet & Ontology (information science). The author has an hindex of 39, co-authored 176 publications receiving 5477 citations. Previous affiliations of German Rigau include Polytechnic University of Catalonia.

Papers
More filters
Proceedings ArticleDOI

SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation

TL;DR: Comunicacio presentada al 10th International Workshop on Semantic Evaluation (SemEval-2016), celebrat els dies 16 i 17 de juny de 2016 a San Diego, California.
Proceedings ArticleDOI

SemEval-2014 Task 10: Multilingual Semantic Textual Similarity

TL;DR: This year, the participants were challenged with new data sets for English, as well as the introduction of Spanish, as a new language in which to assess semantic similarity, and the annotations for both tasks leveraged crowdsourcing.
Proceedings ArticleDOI

Word sense disambiguation using Conceptual Density

TL;DR: In this article, the authors present a method for the resolution of lexical ambiguity of nouns and its automatic evaluation over the Brown Corpus, relying on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a Conceptual Density formula developed for this purpose.
Proceedings ArticleDOI

SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability

TL;DR: This year, the participants were challenged with new datasets in English and Spanish, and the annotations for both subtasks leveraged crowdsourcing, and a pilot task on interpretable STS, where systems needed to add an explanatory layer.
Journal ArticleDOI

Building event-centric knowledge graphs from news

TL;DR: This paper presents an approach to create Event-Centric Knowledge Graphs (ECKGs) using state-of-the-art natural language processing and semantic web techniques, and shows how approaching information from news in an event-centric manner can increase the user's understanding of the domain, facilitates the reconstruction of news story lines, and enable to perform exploratory investigation of news hidden facts.