1 code implementation • COLING 2018 • Matthias Cetto, Christina Niklaus, André Freitas, Siegfried Handschuh
We present an Open Information Extraction (IE) approach that uses a two-layered transformation stage consisting of a clausal disembedding layer and a phrasal disembedding layer, together with rhetorical relation identification.
1 code implementation • COLING 2018 • Matthias Cetto, Christina Niklaus, André Freitas, Siegfried Handschuh
In that way, we preserve the context of the relational tuples extracted from a source sentence, generating a novel lightweight semantic representation for Open IE that enhances the expressiveness of the extracted propositions.
1 code implementation • ACL 2019 • Christina Niklaus, Matthias Cetto, Andre Freitas, Siegfried Handschuh
We present an approach for recursively splitting and rephrasing complex English sentences into a novel semantic hierarchy of simplified sentences, with each of them presenting a more regular structure that may facilitate a wide variety of artificial intelligence tasks, such as machine translation (MT) or information extraction (IE).
1 code implementation • 26 Sep 2019 • Christina Niklaus, Matthias Cetto, Andre Freitas, Siegfried Handschuh
We introduce DisSim, a discourse-aware sentence splitting framework for English and German whose goal is to transform syntactically complex sentences into an intermediate representation that presents a simple and more regular structure which is easier to process for downstream semantic applications.
1 code implementation • 24 May 2021 • Christina Niklaus, Matthias Cetto, André Freitas, Siegfried Handschuh
We present a context-preserving text simplification (TS) approach that recursively splits and rephrases complex English sentences into a semantic hierarchy of simplified sentences.
1 code implementation • COLING 2020 • Thiemo Wambsganss, Christina Niklaus, Matthias Söllner, Siegfried Handschuh, Jan Marco Leimeister
In this paper, we present a novel annotation approach to capture claims and premises of arguments and their relations in student-written persuasive peer reviews on business models in German language.
1 code implementation • ACL 2021 • Thiemo Wambsganss, Christina Niklaus, Matthias Söllner, Siegfried Handschuh, Jan Marco Leimeister
We propose an annotation scheme that allows us to model emotional and cognitive empathy scores based on three types of review components.
1 code implementation • ACL 2022 • Thiemo Wambsganss, Christina Niklaus
We introduce an argumentation annotation approach to model the structure of argumentative discourse in student-written business model pitches.
no code implementations • COLING 2018 • Christina Niklaus, Matthias Cetto, André Freitas, Siegfried Handschuh
We provide a detailed overview of the various approaches that were proposed to date to solve the task of Open Information Extraction.
no code implementations • COLING 2016 • Christina Niklaus, Bernhard Bermeitinger, Siegfried Handschuh, André Freitas
In this demo paper, we present a text simplification approach that is directed at improving the performance of state-of-the-art Open Relation Extraction (RE) systems.
no code implementations • WS 2019 • Christina Niklaus, Andre Freitas, Siegfried Handschuh
We compiled a new sentence splitting corpus that is composed of 203K pairs of aligned complex source and simplified target sentences.
no code implementations • WS 2019 • Christina Niklaus, Matthias Cetto, Andr{\'e} Freitas, H, Siegfried schuh
We introduce DisSim, a discourse-aware sentence splitting framework for English and German whose goal is to transform syntactically complex sentences into an intermediate representation that presents a simple and more regular structure which is easier to process for downstream semantic applications.
no code implementations • COLING (CODI, CRAC) 2022 • Christina Niklaus, André Freitas, Siegfried Handschuh
We present a discourse-aware text simplification (TS) approach that recursively splits and rephrases complex English sentences into a semantic hierarchy of simplified sentences.
no code implementations • 1 Aug 2023 • Christina Niklaus, Matthias Cetto, André Freitas, Siegfried Handschuh
In that way, we generate a semantic hierarchy of minimal propositions that leads to a novel representation of complex assertions that puts a semantic layer on top of the simplified sentences.
no code implementations • 9 Sep 2023 • Johannes Schneider, Bernd Schenk, Christina Niklaus, Michaelis Vlachos
Thus, in this manuscript we provide an evaluation of a large language model for the purpose of autograding, while also highlighting how LLMs can support educators in validating their grading procedures.