Arndt Riester


Combined discourse representations: Coherence relations and questions under Discussion
Arndt Riester | Amalia Canes Nápoles | Jet Hoek
Proceedings of the First Workshop on Integrating Perspectives on Discourse Annotation


QUD-Based Annotation of Discourse Structure and Information Structure: Tool and Evaluation
Kordula De Kuthy | Nils Reiter | Arndt Riester
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

German Radio Interviews: The GRAIN Release of the SFB732 Silver Standard Collection
Katrin Schweitzer | Kerstin Eckart | Markus Gärtner | Agnieszka Falenska | Arndt Riester | Ina Rösiger | Antje Schweitzer | Sabrina Stehwien | Jonas Kuhn
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

Bridging resolution: Task definition, corpus resources and rule-based experiments
Ina Roesiger | Arndt Riester | Jonas Kuhn
Proceedings of the 27th International Conference on Computational Linguistics

Recent work on bridging resolution has so far been based on the corpus ISNotes (Markert et al. 2012), as this was the only corpus available with unrestricted bridging annotation. Hou et al. 2014’s rule-based system currently achieves state-of-the-art performance on this corpus, as learning-based approaches suffer from the lack of available training data. Recently, a number of new corpora with bridging annotations have become available. To test the generalisability of the approach by Hou et al. 2014, we apply a slightly extended rule-based system to these corpora. Besides the expected out-of-domain effects, we also observe low performance on some of the in-domain corpora. Our analysis shows that this is the result of two very different phenomena being defined as bridging, namely referential and lexical bridging. We also report that filtering out gold or predicted coreferent anaphors before applying the bridging resolution system helps improve bridging resolution.


Improving coreference resolution with automatically predicted prosodic information
Ina Roesiger | Sabrina Stehwien | Arndt Riester | Ngoc Thang Vu
Proceedings of the Workshop on Speech-Centric Natural Language Processing

Adding manually annotated prosodic information, specifically pitch accents and phrasing, to the typical text-based feature set for coreference resolution has previously been shown to have a positive effect on German data. Practical applications on spoken language, however, would rely on automatically predicted prosodic information. In this paper we predict pitch accents (and phrase boundaries) using a convolutional neural network (CNN) model from acoustic features extracted from the speech signal. After an assessment of the quality of these automatic prosodic annotations, we show that they also significantly improve coreference resolution.


Using prosodic annotations to improve coreference resolution of spoken text
Ina Roesiger | Arndt Riester
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)


The Extended DIRNDL Corpus as a Resource for Coreference and Bridging Resolution
Anders Björkelund | Kerstin Eckart | Arndt Riester | Nadja Schauffler | Katrin Schweitzer
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

DIRNDL is a spoken and written corpus based on German radio news, which features coreference and information-status annotation (including bridging anaphora and their antecedents), as well as prosodic information. We have recently extended DIRNDL with a fine-grained two-dimensional information status labeling scheme. We have also applied a state-of-the-art part-of-speech and morphology tagger to the corpus, as well as highly accurate constituency and dependency parsers. In the light of this development we believe that DIRNDL is an interesting resource for NLP researchers working on automatic coreference and bridging resolution. In order to enable and promote usage of the data, we make it available for download in an accessible tabular format, compatible with the formats used in the CoNLL and SemEval shared tasks on automatic coreference resolution.


Automatically Acquiring Fine-Grained Information Status Distinctions in German
Aoife Cahill | Arndt Riester
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue


A Recursive Annotation Scheme for Referential Information Status
Arndt Riester | David Lorenz | Nina Seemann
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We provide a robust and detailed annotation scheme for information status, which is easy to use, follows a semantic rather than cognitive motivation, and achieves reasonable inter-annotator scores. Our annotation scheme is based on two main assumptions: firstly, that information status strongly depends on (in)definiteness, and secondly, that it ought to be understood as a property of referents rather than words. Therefore, our scheme banks on overt (in)definiteness marking and provides different categories for each class. Definites are grouped according to the information source by which the referent is identified. A special aspect of the scheme is that non-anaphoric expressions (e.g.\ names) are classified as to whether their referents are likely to be known or unknown to an expected audience. The annotation scheme provides a solution for annotating complex nominal expressions which may recursively contain embedded expressions. In annotating a corpus of German radio news bulletins, a kappa score of .66 for the full scheme was achieved, a core scheme of six top-level categories yields kappa = .78.


Frequency Matters: Pitch Accents and Information Status
Katrin Schweitzer | Michael Walsh | Bernd Möbius | Arndt Riester | Antje Schweitzer | Hinrich Schütze
Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009)

Incorporating Information Status into Generation Ranking
Aoife Cahill | Arndt Riester
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP