most citedMulti-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction

1 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2023

Findings of the VarDial Evaluation Campaign 2023

Noëmi Aepli, Çağrı Çöltekin, Rob Van Der Goot +7

This report presents the results of the shared tasks organized as part of the VarDial Evaluation Campaign 2023. The campaign is part of the tenth workshop on Natural Language Proce…

cs.CL2023

ESCOXLM-R: Multilingual Taxonomy-driven Pre-training for the Job Market Domain

Mike Zhang, Rob van der Goot, Barbara Plank

The increasing number of benchmarks for Natural Language Processing (NLP) tasks in the computational job market domain highlights the demand for methods that can handle job-related…

cs.CL2023

Silver Syntax Pre-training for Cross-Domain Relation Extraction

Elisa Bassignana, Filip Ginter, Sampo Pyysalo +2

Relation Extraction (RE) remains a challenging task, especially when considering realistic out-of-domain evaluations. One of the main reasons for this is the limited training size…

cs.CL20231 cited

Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction

Elisa Bassignana, Filip Ginter, Sampo Pyysalo +2

Most research in Relation Extraction (RE) involves the English language, mainly due to the lack of multi-lingual resources. We propose Multi-CrossRE, the broadest multi-lingual dat…

cs.CL20231 cited

Cross-Domain Evaluation of POS Taggers: From Wall Street Journal to Fandom Wiki

Kia Kirstein Hansen, Rob van der Goot

The Wall Street Journal section of the Penn Treebank has been the de-facto standard for evaluating POS taggers for a long time, and accuracies over 97\% have been reported. However…

cs.CL2021

How Universal is Genre in Universal Dependencies?

Max Müller-Eberstein, Rob van der Goot, Barbara Plank

This work provides the first in-depth analysis of genre in Universal Dependencies (UD). In contrast to prior work on genre identification which uses small sets of well-defined labe…