no code implementations • SEMEVAL 2018 • Tom{\'a}{\v{s}} Brychc{\'\i}n, Tom{\'a}{\v{s}} Hercig, Josef Steinberger, Michal Konkol
We show the word distribution in the corpus has potential for detecting discriminative attributes.
Ranked #4 on Relation Extraction on SemEval 2018 Task 10
no code implementations • IJCNLP 2017 • Michal Konkol, Tom{\'a}{\v{s}} Brychc{\'\i}n, Michal Nykl, Tom{\'a}{\v{s}} Hercig
We implement this principle by comparing the information in the word embeddings with geographical positions of cities.
no code implementations • RANLP 2017 • Michal Konkol
In this paper, we introduce WoRel, a model that jointly learns word embeddings and a semantic representation of word relations.