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The Potsdam Commentary Corpus 2.2: Extending Annotations for Shallow Discourse Parsing

Summary

German has no end-to-end shallow discourse parser, partly because there is little training data annotated in the PDTB style. This paper presents version 2.2 of the Potsdam Commentary Corpus (PCC), a German collection of newspaper opinion pieces. The corpus already carried several annotation layers. Earlier versions marked only explicit connectives and their arguments, with no senses attached.

The authors add two things:

  • Senses for explicit relations, using the PDTB 3.0 sense hierarchy.
  • A new layer for non-explicit relations between adjacent sentences in the same paragraph. These are labelled as implicit (with an inserted connective), AltLex, EntRel or NoRel. The selection rules follow the PDTB 2.0 manual, and senses again follow PDTB 3.0.

Annotators did not use the dedicated tools Connanno or the PDTB Annotator. They entered senses directly into XML attributes and labelled sentence pairs in tab-separated spreadsheets, which were then automatically checked for consistency. The corpus was also revised and moved to standoff XML. The paper reports inter-annotator agreement and compares corpus statistics with the PDTB. The result is a small German counterpart to the PDTB that can be used to train and evaluate shallow discourse parsers.

Key points

  • Corpus size: PCC contains 175 editorials from a German regional newspaper, with just over 34k words in more than 2,100 sentences. The PDTB has over 1m words.
  • Sense hierarchy: PDTB 3.0 senses have three levels: 4 classes (Temporal, Contingency, Comparison, Expansion), 22 types and 28 sub-types.
  • Scope of the new layer: Only inter-sentential non-explicit relations were annotated. Intra-sentential implicit relations, as covered in PDTB 3.0, are left for future work.
  • Earlier releases: PCC 2.1 added aboutness topics, automatic Universal Dependencies parses and access through the ANNIS3 browser. Version 2.2 adds the new layers and converts the connective layer from inline XML to standoff XML.
  • Missing figures: The paper reports agreement scores and PDTB comparison statistics, but these numbers were not in the extracted text provided. Check the original before citing them.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Topics: Discourse analysis

Cited by

27 papers of our library cite it (of the 140673 whose bibliographies we read); 11 of them have a page here, 16 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work.

@inproceedings{bourgonje2020potsdam,
  title = {{The Potsdam Commentary Corpus 2.2: Extending Annotations for Shallow Discourse Parsing}},
  author = {Bourgonje, Peter and Stede, Manfred},
  booktitle = {Proceedings of the Twelfth Language Resources and Evaluation Conference},
  year = {2020},
  url = {https://aclanthology.org/2020.lrec-1.133/}
}

References

27 references, 9 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Bourgonje, P. and Stede, M. (2018a). Identifying Explicit Discourse Connectives in German. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, Melbourne, Australia. find our card
  2. Bourgonje, P. and Stede, M. (2018b). The Potsdam Commentary Corpus 2.1 in ANNIS3. In Proceedings of the 17th International Workshop on Treebanks and Linguistic Theory, Oslo, Norway. find
  3. Bourgonje, P. and Stede, M. (2019). Explicit Discourse Argument Extraction for German. In Proceedings of the 21st International Conference on Text, Speech and Dialogue, Ljubljana, Slovenia. find
  4. Das, D. and Taboada, M. (2018). RST Signalling Corpus: a corpus of signals of coherence relations. Language Resources and Evaluation, 52(1):149–184. ↗
  5. Dipper, S. and Stede, M. (2006). Disambiguating potential connectives. In Proceedings of the KONVENS Conference, Konstanz. find
  6. Hernault, H., Prendinger, H., duVerle, D. A., and Ishizuka, M. (2010). HILDA: A Discourse Parser Using Support Vector Machine Classification. D&D, 1(3):1–33. ↗ our card
  7. Joty, S., Carenini, G., and Ng, R. T. (2015). CODRA: A Novel Discriminative Framework for Rhetorical Analysis. Computational Linguistics, 41(3):385–435, September. ↗ our card
  8. Knott, A., Oberlander, J., O’Donnell, M., Mellish, C., and Mellish, E. M. O. C. (2000). Beyond elaboration: The interaction of relations and focus in coherent text. In Text Representation: Linguistic and Psycholinguistic Aspects, chapter 7, pages 181–196. John Benjamins. find
  9. Krause, T. and Zeldes, A. (2016). ANNIS3: A new architecture for generic corpus query and visualization. Digital Scholarship in the Humanities, 31. find
  10. Lee, A., Prasad, R., Webber, B., and Joshi, A. K. (2016). Annotating discourse relations with the PDTB annotator. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, pages 121–125, Osaka, Japan, December. find
  11. The COLING 2016 Organizing Committee. find
  12. Li, Z., Zhao, H., Pang, C., Wang, L., and Wang, H. (2016). A Constituent Syntactic Parse Tree Based Discourse Parser. In Proceedings of the CONLL 2016 Shared Task, pages 60–64, Berlin. find our card
  13. Lin, Z., Ng, H. T., and Kan, M.-Y. (2014). A PDTB-Styled End-to-End Discourse Parser. Natural Language Engineering, 20:151–184. find
  14. Mann, W. and Thompson, S. (1988). Rhetorical structure theory: Towards a functional theory of text organization. TEXT, 8:243–281. find
  15. Oepen, S., Read, J., Scheffler, T., Sidarenka, U., Stede, M., Velldal, E., and Øvrelid, L. (2016). OPT: Oslo–Potsdam–Teesside—Pipelining Rules, Rankers, and Classifier Ensembles for Shallow Discourse Parsing. In Proceedings of the CONLL 2016 Shared Task, Berlin. find our card
  16. Prasad, R., Dinesh, N., Lee, A., Miltsakaki, E., Robaldo, L., Joshi, A., and Webber, B. (2008). The Penn Discourse Treebank 2.0. In Proc. of the 6th International Conference on Language Resources and Evaluation (LREC), Marrakech, Morocco. find our card
  17. Prasad, R., Webber, B., Lee, A., and Joshi, A. (2019). Penn Discourse Treebank Version 3.0. Philadelphia: Linguistic Data Consortium. ↗
  18. Rysová, M., Jı́nová, P., Mı́rovský, J., Hajičová, E., Nedoluzhko, A., Ocelák, R., Pergler, J., Poláková, L., Zdeňková, J., Scheller, V., and Zikánová, Š. (2016). Prague discourse treebank 2.0. find
  19. Sanders, T., Demberg, V., Hoek, J., Scholman, M., Asr, F., Zufferey, S., and Evers-Vermeul, J. (2018). Unifying dimensions in coherence relations: How various annotation frameworks are related. Corpus Linguistics and Linguistic Theory, 05. ↗
  20. Soricut, R. and Marcu, D. (2003). Sentence level discourse parsing using syntactic and lexical information. In Proceedings of the 2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics. find our card
  21. Stede, M. and Heintze, S. (2004). Machine-assisted rhetorical structure annotation. In Proceedings of the 20th International Conference on Computational Linguistics, COLING ’04, Stroudsburg, PA, USA. Association for Computational Linguistics. find
  22. Stede, M. and Neumann, A. (2014). Potsdam Commentary Corpus 2.0: Annotation for discourse research. In Proceedings of the International Conference on Language Resources and Evaluation (LREC), pages 925– 929, Reikjavik. find
  23. Stede, M. (2004). Kontrast im Diskurs. In H. Blühdorn, et al., editors, Brücken schlagen. Grundlagen der Kon-nektorensemantik, pages 255–286. Walter de Gruyter, Berlin. ↗
  24. Wang, J. and Lan, M. (2015). A Refined End-to-End Discourse Parser. In Proceedings of the Nineteenth Conference on Computational Natural Language Learning - Shared Task, pages 17–24. Association for Computational Linguistics. find our card
  25. Zeldes, A., Das, D., Maziero, E. G., Antonio, J., and Iruskieta, M. (2019). find
  26. The DISRPT 2019 Shared Task on Elementary Discourse Unit Segmentation and Connective Detection. In Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019, pages 97–104, Minneapolis, MN, June. Association for Computational Linguistics. find our card
  27. Zeyrek, D., Mendes, A., Grishina, Y., Kurfalı, M., Gibbon, S., and Ogrodniczuk, M. (2019). TED Multilingual Discourse Bank (TED-MDB): a parallel corpus annotated in the PDTB style. Language Resources and Evaluation, 04. ↗

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