Search Results for author: Christina Niklaus

Found 12 papers, 8 papers with code

Modeling Persuasive Discourse to Adaptively Support Students’ Argumentative Writing

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.

Supporting Cognitive and Emotional Empathic Writing of Students

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.

Context-Preserving Text Simplification

1 code implementation24 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.

Text Simplification

A Corpus for Argumentative Writing Support in German

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.

DisSim: A Discourse-Aware Syntactic Text Simplification Framework for English and German

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.

Text Simplification

MinWikiSplit: A Sentence Splitting Corpus with Minimal Propositions

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.

Text Simplification

DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English and German

1 code implementation26 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.

Text Simplification

Transforming Complex Sentences into a Semantic Hierarchy

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).

Machine Translation Text Simplification +1

Graphene: A Context-Preserving Open Information Extraction System

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.

Open Information Extraction

Graphene: Semantically-Linked Propositions in Open Information Extraction

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.

Open Information Extraction

A Survey on Open Information Extraction

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.

Open Information Extraction

A Sentence Simplification System for Improving Relation 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.

Relation Extraction Text Simplification

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