Using a unified taxonomy to annotate discourse markers in speech and writing
Summary
Descriptions of discourse markers (DMs) are usually built for either speech or writing, even though many markers such as so or because occur in both. Crible and Zufferey test whether one sense taxonomy can serve both modes. The taxonomy (Crible, 2014) was first developed on spoken French and English. It has 29 values grouped into four domains: ideational, rhetorical, sequential and interpersonal. Annotators may assign two tags to a single token.
Two expert coders worked on short English and French texts:
- Spoken data: interviews from the Backbone corpus.
- Written data: newspaper articles from the COMTIS project.
The coders first identified candidate DMs and then annotated their senses. Agreement on spoken data was not lower than on written data, contrary to what was expected. The two modes differed mainly in the kinds of disagreement they produced. Each coder's background in speech or writing also biased their choices.
The paper's main value is methodological. It shows that coder training, explicit criteria and paraphrases for each tag make sense annotation more reliable. It also moves toward a single multimodal scheme instead of many incompatible frameworks.
Key points
- Data: four texts of about 1000 words each, covering spoken and written English and French. Spoken texts come from Backbone (Kurt, 2012) and written texts from COMTIS newspaper articles.
- Identification agreement: relative agreement on DM selection was 82.25% for spoken English and 87.34% for spoken French. It was 79.16% for written English and 66.67% for written French.
- Coder bias: the coder specialised in writing selected more DMs in the written texts (28 vs. 20 in English, 26 vs. 19 in French). The same coder was also more willing to label written uses as rhetorical or "pragmatic".
- Comparison with PDTB: unlike the Penn Discourse Treebank's hierarchical sense levels, the scheme separates domain-specific pairs at the first level, for example ideational cause vs. rhetorical motivation.
- Learning effect: sense-annotation agreement rose from the first to the second annotation within a language, but the gain did not carry over across languages. The authors take this as a sign that DM usage is partly language-specific.
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Cite
@inproceedings{crible2015using,
title = {{Using a unified taxonomy to annotate discourse markers in speech and writing}},
author = {Crible, Ludivine and Zufferey, Sandrine},
booktitle = {Proceedings of the 11th Joint ACL-ISO Workshop on Interoperable Semantic Annotation (ISA-11)},
year = {2015},
url = {https://aclanthology.org/W15-0202/}
}References
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