no code implementations • GermEval 2021 • Mina Schütz, Christoph Demus, Jonas Pitz, Nadine Probol, Melanie Siegel, Dirk Labudde
For this binary task, we propose three models: a German BERT transformer model; a multilayer perceptron, which was first trained in parallel on textual input and 14 additional linguistic features and then concatenated in an additional layer; and a multilayer perceptron with both feature types as input.
no code implementations • EACL (GWC) 2021 • Melanie Siegel, Francis Bond
In a relatively short time a resource was created that can be used in projects and continuously improved and extended.
no code implementations • GWC 2019 • Thierry Declerck, Melanie Siegel
In this paper we describe our current work on representing a recently created German lexical semantics resource in OntoLex-Lemon and in conformance with WordNet specifications.
1 code implementation • NAACL (WOAH) 2022 • Christoph Demus, Jonas Pitz, Mina Schütz, Nadine Probol, Melanie Siegel, Dirk Labudde
In this work, we present a new publicly available offensive language dataset of 10. 278 German social media comments collected in the first half of 2021 that were annotated by in total six annotators.
no code implementations • 5 Jun 2023 • Margot Madina, Itziar Gonzalez-Dios, Melanie Siegel
Plain Language (PL), on the other hand, is a variant of a given language, which aims to promote the use of simple language to communicate information.
no code implementations • 7 Mar 2023 • Fabian Sturm, Elke Hergenroether, Julian Reinhardt, Petar Smilevski Vojnovikj, Melanie Siegel
This work presents the Industrial Hand Action Dataset V1, an industrial assembly dataset consisting of 12 classes with 459, 180 images in the basic version and 2, 295, 900 images after spatial augmentation.
no code implementations • LREC 2020 • Thierry Declerck, Lenka Bajcetic, Melanie Siegel
We describe on-going work consisting in adding pronunciation information to wordnets, as such information can indicate specific senses of a word.
no code implementations • WS 2019 • Thierry Declerck, Melanie Siegel, Stefania Racioppa
We show how the Multiword Expressions (MWEs) contained in OdeNet can be morphologically specified by the use of the lexical representation and linking features of OntoLex-Lemon, which also support the formulation of restrictions in the usage of such expressions.