Papers by Peter Bourgonje
Shallow Discourse Parsing for Under-Resourced Languages: Combining Machine Translation and Annotation Projection (2020.lrec-1)
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| Challenge: | Shallow Discourse Parsing (SDP) relies on large amounts of training data, which so far exists only for English. |
| Approach: | They propose to translate an existing English Penn Discourse TreeBank into German and use it to create a German corpus annotated for shallow discourse relations in the news domain. |
| Outcome: | The proposed corpus is annotated for shallow discourse relations in the (financial) news domain. |
Automatic and Manual Web Annotations in an Infrastructure to handle Fake News and other Online Media Phenomena (L18-1)
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| Challenge: | a growing number of people consume news online, but there are different types of "fake news" many online news outlets use the same journalistic principles that have been in use for newspapers for decades, especially factchecking. |
| Approach: | They propose a metadata scheme to enable users to handle "fake news" they also propose 'filter bubble' effect and abuse language . |
| Outcome: | The proposed metadata scheme enables standardisation of these phenomena in online media. |
How Diplomats Dispute: The UN Security Council Conflict Corpus (2024.lrec-main)
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| Challenge: | Until now, there has been little work on how to formalize conflicts in a diplomatic setting. |
| Approach: | They present a corpus of 87 UNSC speeches that are annotated for conflicts and demonstrate the difficulty when dealing with diplomatic language. |
| Outcome: | The proposed method demonstrates that diplomatic language is complex and often implicit along various dimensions. |
Implicit Discourse Relation Classification For Nigerian Pidgin (2025.coling-main)
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| Challenge: | Existing discourse parsing tools are not available for Nigerian Pidgin (NP) this task requires supervised training and requires prompting. |
| Approach: | They propose to use implicit discourse relation classification (IDRC) for Nigerian Pidgin, which requires supervised training. |
| Outcome: | The proposed framework outperforms baseline and NP IDR classifiers in f1 scores. |
The Potsdam Commentary Corpus 2.2: Extending Annotations for Shallow Discourse Parsing (2020.lrec-1)
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| Challenge: | Potsdam Commentary Corpus 2.2 is a german corpus of news editorials annotated on several levels. |
| Approach: | They propose to add relation senses to an already existing layer of discourse connectives and their arguments and a new layer with additional coherence relation types to the potsdam commentary corpus. |
| Outcome: | The proposed corpus is more usable for shallow discourse parsing. |
Making a Semantic Event-type Ontology Multilingual (2022.lrec-1)
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| Challenge: | a new version of SynSemClass is being developed for use in natural language processing . the ontology is a bilingual resource with no links to a valency lexicon . |
| Approach: | They propose to add German entries to the SynSemClass Event-type Ontology . they propose to use the ontology as a human-readable and human-understandable database . |
| Outcome: | The proposed extension of SynSemClass Event-type Ontology is presented in a paper in czech republic . the ontology provides curated data for NLP experiments with cross-lingual synonyms . |
Abstractive Text Summarization based on Language Model Conditioning and Locality Modeling (2020.lrec-1)
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Dmitrii Aksenov, Julian Moreno-Schneider, Peter Bourgonje, Robert Schwarzenberg, Leonhard Hennig, Georg Rehm
| Challenge: | Abstractive summarization is an NLP task with many real-world applications. |
| Approach: | They propose to use a pre-trained language model to train a Transformer-based neural model . they propose a new method of BERT-windowing to allow chunk-wise processing of texts longer than the BERT window size . |
| Outcome: | The proposed model outperforms baseline models on CNN/Daily Mail dataset and shows its superiority on German dataset. |
Exploiting a lexical resource for discourse connective disambiguation in German (2020.coling-main)
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| Challenge: | a connective lexicon can be a valuable resource for languages with limited PDTB-style annotations . connectives are usually understood to be ambiguous in two different ways . |
| Approach: | They propose to augment a purely-empirical approach to connective identification and sense classification in German . they find that a connective lexicon can be a valuable resource for those languages with a large PDTB-style-annotated coprus . |
| Outcome: | The proposed approach improves on published results and achieves an F1 score for German sense classification. |