Papers by Ines Rehbein
Our kind of people? Detecting populist references in political debates (2023.findings-eacl)
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| Challenge: | Existing literature on populism has only limited agreement on its exact properties . |
| Approach: | They propose a cross-lingual dataset to identify populist rhetoric in text . they propose 'hierarchical' annotation procedure to annotate populist references . |
| Outcome: | The proposed dataset can be used to investigate how political actors talk about The Elite and The People and to study how populist rhetoric is used as a strategic device. |
Parsers Know Best: German PP Attachment Revisited (2020.coling-main)
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| Challenge: | PP attachment is one of the major sources of parser errors and is still one of hardest problems for syntactic parsing. |
| Approach: | They present a realistic evaluation of the potential of different PP attachment systems using fully predicted information as system input. |
| Outcome: | The proposed approach is superior to modelling PP attachment disambiguation as a separate task. |
Out of the Mouths of MPs: Speaker Attribution in Parliamentary Debates (2024.lrec-main)
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| Challenge: | Identifying who says what to whom is an essential prerequisite for analysing human communication. |
| Approach: | They propose a new corpus for speaker attribution in german parliamentary debates . the data includes more than 7,700 manually annotated events of speech, thought and writing . they then apply their model to predict speech events in 20 years of debates and investigate the use of factives in the rhetoric of MPs. |
| Outcome: | The proposed model predicts speech events in 20 years of debates and investigates the use of factives in the rhetoric of MPs. |
Who’s in, who’s out? Predicting the Inclusiveness or Exclusiveness of Personal Pronouns in Parliamentary Debates (2022.lrec-1)
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| Challenge: | clusivity properties of personal pronouns are captured in context, including/excluding audience and/or non-speech act participants. |
| Approach: | They propose a compositional annotation scheme to capture the clusivity properties of personal pronouns in context, which is their ability to construct and manage in-groups and out-group. |
| Outcome: | The proposed schema achieves high inter-annotator agreement with a Cohen’s in the range of 89.7-93.2 and a percentage agreement of > 96%. |
How to Do Politics with Words: Investigating Speech Acts in Parliamentary Debates (2024.lrec-main)
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| Challenge: | a new perspective on framing through the lens of speech acts investigates how politicians make use of different pragmatic speech act functions in political debates. |
| Approach: | They propose a new framework for framing through the lens of speech acts and an annotation scheme for political debates. |
| Outcome: | The proposed framework can predict speech acts with an avg. F1 of around 82.0% . the proposed framework is based on a dataset of German parliamentary debates . |
Come hither or go away? Recognising pre-electoral coalition signals in the news (2021.emnlp-main)
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Ines Rehbein, Simone Paolo Ponzetto, Anna Adendorf, Oke Bahnsen, Lukas Stoetzer, Heiner Stuckenschmidt
| Challenge: | In this paper, we decompose the task of recognizing from the news coverage leading up to an election the (un)willingness of political parties to form a coalition into two related, but distinct tasks. |
| Approach: | They propose a task of recognizing from news coverage the (un)willingness of political parties to form a coalition from text and a sub-task of predicting the polarity of the signal. |
| Outcome: | The proposed approach improves over a strong monolingual transfer learning baseline. |
Sprucing up the trees – Error detection in treebanks (C18-1)
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| Challenge: | a method for detecting annotation errors in manually annotated dependency trees is presented . the method is based on ensemble parsing and Bayesian inference guided by active learning . |
| Approach: | They propose a method for detecting annotation errors in manually annotated dependency parse trees . they use ensemble parsing in combination with Bayesian inference guided by active learning . |
| Outcome: | The proposed method detects errors in annotated dependency treebanks and improves parsing accuracy on in- and out-of-domain data. |
Neural Reranking for Dependency Parsing: An Evaluation (2020.acl-main)
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| Challenge: | Recent work shows that neural rerankers can improve dependency parsing results over the top k trees produced by a base parser. |
| Approach: | They propose to use a discriminative reranker to improve dependency parsing results . they propose to incorporate global information into the model to improve parse accuracies . |
| Outcome: | The proposed model outperforms existing models on English and German and Czech, and is the only one to improve on German and Chinese data. |
Fine-grained Named Entity Annotations for German Biographic Interviews (2020.lrec-1)
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| Challenge: | a NER annotation scheme is adapted for a corpus of transcripts of biographic interviews with emigrants to German . a dataset of spoken data and teaser tweets from newspaper sites are used to test the NER inventory. |
| Approach: | They propose a fine-grained NER annotation scheme with 30 labels and apply it to German data. |
| Outcome: | The proposed NER annotations can be applied to spoken data and teaser tweets from newspaper sites and achieve good inter-annotator agreement. |
A New Resource for German Causal Language (2020.lrec-1)
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| Challenge: | Annotations of causal language are challenging for automatic and human annotators. |
| Approach: | They propose a German causal annotation resource with annotations in context for verbs, nouns and prepositions. |
| Outcome: | The proposed annotation scheme distinguishes three types of causal events . the proposed framework also provides annotations for semantic roles and actors . |
Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies (2020.lrec-1)
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Manuela Sanguinetti, Cristina Bosco, Lauren Cassidy, Özlem Çetinoğlu, Alessandra Teresa Cignarella, Teresa Lynn, Ines Rehbein, Josef Ruppenhofer, Djamé Seddah, Amir Zeldes
| Challenge: | Despite the increasing number of contributions on Part-of-Speech tagging and parsing, automatic processing of user-generated content (UGC) still represents a challenging task. |
| Approach: | They propose a set of guidelines for the annotation of user-generated texts within the Universal Dependencies framework. |
| Outcome: | The proposed annotation guidelines promote cross-linguistic consistency, which has always been in the spirit of UD. |
Moral Framing in Politics (MFiP): A new resource and models for moral framing (2025.emnlp-main)
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| Challenge: | Recent studies have focused on detecting moral values in political communication, trying to identify moral frames used by political actors or parties to convey their messages. |
| Approach: | They propose to code German parliamentary debates to identify moral framing and to detect subtle differences in politicians’ moral framming. |
| Outcome: | The proposed model distinguishes between different types of moral frames and includes narrative roles, together with the moral foundations for each frame. |
Improving Sentence Boundary Detection for Spoken Language Transcripts (2020.lrec-1)
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| Challenge: | Using data expansion and transfer learning, we find that data expansion does not always improve results. |
| Approach: | They propose to divide spoken language into sentence-like units using Topological Fields model . they also propose to use data from the same domain to test different ML architectures . |
| Outcome: | The proposed model improves the detection of boundary detection in spoken dialogues compared to a sequence tagging approach. |
A Survey on Modelling Morality for Text Analysis (2024.findings-acl)
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| Challenge: | Recent work on modelling morality in text has garnered increasing attention due to its complexity and complexity. |
| Approach: | They provide a systematic review of recent work on modelling morality in text . they discuss challenges and research gaps in the area of NLP . |
| Outcome: | The authors present their work on the modelling of morality in text, which has garnered increasing attention in recent years. |