Search Results for author:
Found 33 papers, 5 papers with code
Political Text Scaling Meets Computational Semantics
During the last fifteen years, automatic text scaling has become one of the key tools of the Text as Data community in political science.
FrameASt: A Framework for Second-level Agenda Setting in Parliamentary Debates through the Lense of Comparative Agenda Topics
In addition, we present a new annotated data set of parliamentary debates, following the coding schema of policy topics developed in the Comparative Agendas Project (CAP), and release models for topic classification in parliamentary debates.
Active Learning via Membership Query Synthesis for Semi-Supervised Sentence Classification
Active learning (AL) is a technique for reducing manual annotation effort during the annotation of training data for machine learning classifiers.
Exploring Morality in Argumentation
Sentiment and stance are two important concepts for the analysis of arguments.
Detecting annotation noise in automatically labelled data
We introduce a method for error detection in automatically annotated text, aimed at supporting the creation of high-quality language resources at affordable cost.
Catching the Common Cause: Extraction and Annotation of Causal Relations and their Participants
In this paper, we present a simple, yet effective method for the automatic identification and extraction of causal relations from text, based on a large English-German parallel corpus.
What do we need to know about an unknown word when parsing German
We propose a new type of subword embedding designed to provide more information about unknown compounds, a major source for OOV words in German.
Authorship Attribution with Convolutional Neural Networks and POS-Eliding
We use a convolutional neural network to perform authorship identification on a very homogeneous dataset of scientific publications.
Evaluating LSTM models for grammatical function labelling
To improve grammatical function labelling for German, we augment the labelling component of a neural dependency parser with a decision history.
Sprucing up the trees -- Error detection in treebanks
We present a method for detecting annotation errors in manually and automatically annotated dependency parse trees, based on ensemble parsing in combination with Bayesian inference, guided by active learning.
The KiezDeutsch Korpus (KiDKo) Release 1.0
This paper presents the first release of the KiezDeutsch Korpus (KiDKo), a new language resource with multiparty spoken dialogues of Kiezdeutsch, a newly emerging language variety spoken by adolescents from multiethnic urban areas in Germany.
Yes we can!? Annotating English modal verbs
This paper presents an annotation scheme for English modal verbs together with sense-annotated data from the news domain.
Automatic Alignment and Annotation Projection for Literary Texts
This paper presents a modular NLP pipeline for the creation of a parallel literature corpus, followed by annotation transfer from the source to the target language.
Annotating Discourse Relations in Spoken Language: A Comparison of the PDTB and CCR Frameworks
In discourse relation annotation, there is currently a variety of different frameworks being used, and most of them have been developed and employed mostly on written data.
On the role of discourse relations in persuasive texts
We present a corpus study where we control for speaker and topic and show that the distribution of different discourse connectives varies considerably across different discourse settings.
Fine-grained Named Entity Annotations for German Biographic Interviews
Building on the OntoNotes 5. 0 NER inventory, our scheme is adapted for a corpus of transcripts of biographic interviews by adding categories for AGE and LAN(guage) and also features extended numeric and temporal categories.
Treebanking User-Generated Content: A Proposal for a Unified Representation in Universal Dependencies
The paper presents a discussion on the main linguistic phenomena of user-generated texts found in web and social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework.
A New Resource for German Causal Language
In the paper, we present inter-annotator agreement scores for our dataset and discuss problems for annotating causal language.
Improving Sentence Boundary Detection for Spoken Language Transcripts
For the detection of boundaries in spoken language transcripts, we achieve a substantial improvement when framing the boundary detection problem assentence pair classification task, as compared to a sequence tagging approach.
Neural Reranking for Dependency Parsing: An Evaluation
We show that the GCN not only outperforms previous models on English but is the only model that is able to improve results over the baselines on German and Czech.
Treebanking User-Generated Content: a UD Based Overview of Guidelines, Corpora and Unified Recommendations
This article presents a discussion on the main linguistic phenomena which cause difficulties in the analysis of user-generated texts found on the web and in social media, and proposes a set of annotation guidelines for their treatment within the Universal Dependencies (UD) framework of syntactic analysis.
Parsers Know Best: German PP Attachment Revisited
In particular, we show that using gold information for the extraction of attachment candidates as well as a missing comparison of the system{'}s output to the output of a full syntactic parser leads to an overly optimistic assessment of the results.
I’ve got a construction looks funny – representing and recovering non-standard constructions in UD
We argue that a unified treatment of constructions across languages will increase the consistency of the UD annotations and thus the quality of the treebanks for linguistic analysis.
Come hither or go away? Recognising pre-electoral coalition signals in the news
In this paper, we introduce the task of political coalition signal prediction from text, that is, the task of recognizing from the news coverage leading up to an election the (un)willingness of political parties to form a government coalition.
Who is we? Disambiguating the referents of first person plural pronouns in parliamentary debates
This paper investigates the use of first person plural pronouns as a rhetorical device in political speeches.
Who’s in, who’s out? Predicting the Inclusiveness or Exclusiveness of Personal Pronouns in Parliamentary Debates
This paper presents a compositional annotation scheme to capture the clusivity properties of personal pronouns in context, that is their ability to construct and manage in-groups and out-groups by including/excluding the audience and/or non-speech act participants in reference to groups that also include the speaker.
