Cross-Lingual Link Discovery for Under-Resourced Languages

no code implementations • LREC 2022 • Michael Rosner, Sina Ahmadi, Elena-Simona Apostol, Julia Bosque-Gil, Christian Chiarcos, Milan Dojchinovski, Katerina Gkirtzou, Jorge Gracia, Dagmar Gromann, Chaya Liebeskind, Giedrė Valūnaitė Oleškevičienė, Gilles Sérasset, Ciprian-Octavian Truică

In this paper, we provide an overview of current technologies for cross-lingual link discovery, and we discuss challenges, experiences and prospects of their application to under-resourced languages.

A Survey of Guidelines and Best Practices for the Generation, Interlinking, Publication, and Validation of Linguistic Linked Data

no code implementations • LDL (ACL) 2022 • Fahad Khan, Christian Chiarcos, Thierry Declerck, Maria Pia di Buono, Milan Dojchinovski, Jorge Gracia, Giedre Valunaite Oleskeviciene, Daniela Gifu

This article discusses a survey carried out within the NexusLinguarum COST Action which aimed to give an overview of existing guidelines (GLs) and best practices (BPs) in linguistic linked data.

DBpedia NIF: Open, Large-Scale and Multilingual Knowledge Extraction Corpus

no code implementations • 26 Dec 2018 • Milan Dojchinovski, Julio Hernandez, Markus Ackermann, Amit Kirschenbaum, Sebastian Hellmann

The aim of the dataset is two-fold: to dramatically broaden and deepen the amount of structured information in DBpedia, and to provide large-scale and multilingual language resource for development of various NLP and IR task.

FREME: Multilingual Semantic Enrichment with Linked Data and Language Technologies

no code implementations • LREC 2016 • Milan Dojchinovski, Felix Sasaki, Tatjana Gornostaja, Sebastian Hellmann, Erik Mannens, Frank Salliau, Michele Osella, Phil Ritchie, Giannis Stoitsis, Kevin Koidl, Markus Ackermann, Nilesh Chakraborty

In the recent years, Linked Data and Language Technology solutions gained popularity.

Translation

DBpedia Abstracts: A Large-Scale, Open, Multilingual NLP Training Corpus

no code implementations • LREC 2016 • Martin Br{\"u}mmer, Milan Dojchinovski, Sebastian Hellmann

The ever increasing importance of machine learning in Natural Language Processing is accompanied by an equally increasing need in large-scale training and evaluation corpora.

Entity Linking Multilingual NLP

Crowdsourced Corpus with Entity Salience Annotations

no code implementations • LREC 2016 • Milan Dojchinovski, Dinesh Reddy, Tom{\'a}{\v{s}} Kliegr, Tom{\'a}{\v{s}} Vitvar, Harald Sack

In this paper, we present a crowdsourced dataset which adds entity salience (importance) annotations to the Reuters-128 dataset, which is subset of Reuters-21578.