Is there less annotator agreement when the discourse relation is underspecified?
Written for the Research library (claude-opus-5-5) from the paper text. Original — aclanthology.org/2021.discann-1.1.pdf
Summary
People who annotate coherence relations tend to agree less on implicit relations than on relations marked by a connective. The authors test one explanation: implicit relations require more inference. If that were the main cause, agreement should drop as the marker becomes less specific.
They sampled 350 relations from English TED talk transcripts, drawn from TED-MDB and the Ted Corpus Search Engine:
- 150 marked by specific connectives (because, in addition, even though)
- 100 marked by underspecified ones (and, but)
- 100 with no connective
Two expert coders labelled every relation using the CCR framework, and a third coder settled disagreements. Agreement on full labels was measured with percentage agreement, Cohen's Kappa and Gwet's AC1.
Explicit relations did reach higher agreement than implicit ones. However, underspecified relations did not land in between. Relations with and scored about as well as those with specific connectives, while but produced the weakest agreement of all. Connective specificity alone therefore cannot explain why discourse annotation is hard, which matters for guideline design and for interpreting corpus labels.
Key points
-
Data sources: All 47 but-relations and 50 and-relations came from TED-MDB, plus 3 extra but-relations from the search engine. The annotated dataset was released publicly.
-
Agreement scores (%, κ, AC1):
Marker % κ AC1 because 84 .68 .68 and 74 .58 .71 implicit 66 .58 .64 but 58 .39 .46 -
Why and beat but: The authors link this to and's stronger default reading. 78% of and-relations were positive additive, compared with 66% of but-relations being negative additive.
-
Source of but disagreements: Most concerned BASIC OPERATION, i.e. the notoriously hard split between contrast (negative additive) and concession (negative causal).
-
Implicit relations: These showed the widest variety of labels, and several relations can hold at once. ORDER OF THE SEGMENTS was excluded from the analysis because it was trivial for specific connectives (100% agreement).
Cited by
- Exploring Soft-Label Training for Implicit Discourse Relation Recognition
- Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training
- DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations
Cite
@inproceedings{hoek2021is,
title = {{Is there less annotator agreement when the discourse relation is underspecified?}},
author = {Hoek, Jet and Scholman, Merel C.J. and Sanders, Ted J.M.},
booktitle = {Proceedings of the First Workshop on Integrating Perspectives on Discourse Annotation},
year = {2021},
url = {https://aclanthology.org/2021.discann-1.1/}
}References
- Ron Artstein and Massimo Poesio. 2008. Inter-coder agreement for computational linguistics. Computational Linguistics, 34(4):555–596. find
- Fatemeh Torabi Asr and Vera Demberg. 2012. Implicitness of discourse relations. In Proceedings of COL-ING 2012, pages 2669–2684. find our card
- Bruce K. Britton. 1994. Understanding expository text: Building mental structures to induce insights. Academic Press. find
- Anneloes R. Canestrelli, Willem M. Mak, and Ted J.M. Sanders. 2013. Causal connectives in discourse processing: How differences in subjectivity are reflected in eye movements. Language and Cognitive Processes, 28(9):1394–1413. find
- Jacob Cohen. 1960. A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1):37–46. find
- Ludivine Crible, Ágnes Abuczki, Nijolė Burkšaitienė, Péter Furkó, Anna Nedoluzhko, Sigita Rack-evičienė, Giedrė Valūnaitė Oleškevičienė, and Šárka Zikánová. 2019. Functions and translations of discourse markers in ted talks: A parallel corpus study of underspecification in five lan… find
- Liesbeth Degand and Sandrine Zufferey. 2013. Annotating the meaning of discourse connectives in multilingual corpora. Corpus linguistics and linguistic theory, pages 1–24. find
- Jacqueline Evers-Vermeul, Jet Hoek, and Merel C.J. Scholman. 2017. On temporality in discourse annotation: Theoretical and practical considerations. Dialogue & Discourse, 8(2):1–20. find
- Alvan R. Feinstein and Domenic V. Cicchetti. 1990. High agreement but low kappa: I. The problems of two paradoxes. Journal of clinical epidemiology, 43(6):543–549. find
- Morton Ann Gernsbacher. 1997. Coherence cues mapping during comprehension. Processing inter-clausal relationships. Studies in the production and comprehension of text, pages 3–22. find
- Kilem Gwet. 2001. Handbook of inter-rater reliability: How to estimate the level of agreement between two or multiple raters. Gaithersburg, MD: STATAXIS Publishing Company. find
- Yoichiro Hasebe. 2015. Design and implementation of an online corpus of presentation transcripts of ted talks. Procedia: Social and Behavioral Sciences, 24:174–182. find
- Jet Hoek, Jacqueline Evers-Vermeul, and Ted J.M. Sanders. 2019. Using the cognitive approach to coherence relations for discourse annotation. Dialogue & Discourse, 10(2):1–33. find
- Jet Hoek and Merel C.J. Scholman. 2017. Evaluating discourse annotation: Some recent insights and new approaches. In Proceedings of the 13th Joint ISO-ACL Workshop on Interoperable Semantic Annotation (ISA-13), pages 1–13, Toulouse, France. find
- Jet Hoek, Sandrine Zufferey, Jacqueline Evers-Vermeul, and Ted J M Sanders. 2017. Cognitive complexity and the linguistic marking of coherence relations: A parallel corpus study. Journal of Pragmatics, 121:113–131. find
- Eleni Miltsakaki, Aravind Joshi, Rashmi Prasad, and Bonnie Webber. 2004. Annotating discourse connectives and their arguments. In Proceedings of the Workshop Frontiers in Corpus Annotation at HLT-NAACL 2004, pages 9–16, Boston, MA, USA. find our card
- Rashmi Prasad, Nikhil Dinesh, Alan Lee, Eleni Milt-sakaki, Livio Robaldo, Aravind K. Joshi, and Bonnie Webber. 2008. The Penn Discourse TreeBank 2.0. In Proceedings of the 6th International Conference on Language Resources and Evaluation (LREC), pages 2961–2968, Marrakech, Marocco. find our card
- Ines Rehbein, Merel C. J. Scholman, and Vera Demberg. 2016. Annotating discourse relations in spoken language: A comparison of the PDTB and CCR frameworks. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC), pages 23–28, Portoroz, Slovenia. find our card
- Livio Robaldo and Eleni Miltsakaki. 2014. Corpus-driven semantics of concession: Where do expectations come from? Dialogue & Discourse, 5(1):1– 36. find
- Hannah Rohde, Alexander Johnson, Nathan Schneider, and Bonnie Webber. 2018. Discourse coherence: Concurrent explicit and implicit relations. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2257–2267. find our card
- Ted J. M. Sanders, Vera Demberg, Jet Hoek, Merel C. J. Scholman, Fatemeh Torabi Asr, Sandrine Zufferey, and Jacqueline Evers-Vermeul. 2018. Unifying dimensions in discourse relations: How various annotation frameworks are related. Corpus Linguistics and Linguistic Theory, ahead of print:1–71. find
- Ted J. M. Sanders and Leo G. M. Noordman. 2000. The role of coherence relations and their linguistic markers in text processing. Discourse Processes, 29(1):37–60. find
- Ted J.M. Sanders, Wilbert P.M.S. Spooren, and Leo G.M. Noordman. 1992. Toward a taxonomy of coherence relations. Discourse Processes, 15(1):1– 35. find
- Merel C. J. Scholman and Vera Demberg. 2017. Examples and specifications that prove a point: Identifying elaborative and argumentative discourse relations. Dialogue & Discourse, 8(2):56–83. find our card
- Wilbert Spooren. 1997. The processing of underspecified coherence relations. Discourse Processes, 24(1):149–168. find
- Wilbert P.M.S. Spooren and Liesbeth Degand. 2010. Coding coherence relations: Reliability and validity. Corpus Linguistics and Linguistic Theory, 6(2):241– 266. find
- Deniz Zeyrek, Amália Mendes, Yulia Grishina, Murathan Kurfalı, Samuel Gibbon, and Maciej Ogrodniczuk. 2019. Ted multilingual discourse bank (TED-MDB): a parallel corpus annotated in the PDTB style. Language Resources and Evaluation, pages 1–27. find