no code implementations • LREC 2020 • Kristian Noullet, Rico Mix, Michael F{\"a}rber
Therefore, we have extended a widely-used gold standard data set, KORE 50, to not only accommodate NERD tasks for DBpedia, but also for YAGO, Wikidata and Crunchbase.
no code implementations • LREC 2020 • Sora Lim, Adam Jatowt, Michael F{\"a}rber, Masatoshi Yoshikawa
In this paper, we propose a novel news bias dataset which facilitates the development and evaluation of approaches for detecting subtle bias in news articles and for understanding the characteristics of biased sentences.
1 code implementation • SEMEVAL 2019 • Michael F{\"a}rber, Agon Qurdina, Lule Ahmedi
In this paper, we present an approach for classifying news articles as biased (i. e., hyperpartisan) or unbiased, based on a convolutional neural network.
no code implementations • LREC 2014 • Lei Zhang, Michael F{\"a}rber, Achim Rettinger
In this paper, we introduce our cross-lingual linked data lexica, called xLiD-Lexica, which are constructed by exploiting the multilingual Wikipedia and linked data resources from Linked Open Data (LOD).