Abstract
Full text discourse parsing relies on texts comprehensively annotated with discourse relations. To this end, we address a significant gap in the inter-sentential discourse relations annotated in the Penn Discourse Treebank (PDTB), namely the class of cross-paragraph implicit relations, which account for 30% of inter-sentential relations in the corpus. We present our annotation study to explore the incidence rate of adjacent vs. non-adjacent implicit relations in cross-paragraph contexts, and the relative degree of difficulty in annotating them. Our experiments show a high incidence of non-adjacent relations that are difficult to annotate reliably, suggesting the practicality of backing off from their annotation to reduce noise for corpus-based studies. Our resulting guidelines follow the PDTB adjacency constraint for implicits while employing an underspecified representation of non-adjacent implicits, and yield 62% inter-annotator agreement on this task.- Anthology ID:
- W17-5502
- Volume:
- Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
- Month:
- August
- Year:
- 2017
- Address:
- Saarbrücken, Germany
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 7–16
- Language:
- URL:
- https://aclanthology.org/W17-5502
- DOI:
- 10.18653/v1/W17-5502
- Cite (ACL):
- Rashmi Prasad, Katherine Forbes Riley, and Alan Lee. 2017. Towards Full Text Shallow Discourse Relation Annotation: Experiments with Cross-Paragraph Implicit Relations in the PDTB. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, pages 7–16, Saarbrücken, Germany. Association for Computational Linguistics.
- Cite (Informal):
- Towards Full Text Shallow Discourse Relation Annotation: Experiments with Cross-Paragraph Implicit Relations in the PDTB (Prasad et al., SIGDIAL 2017)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/W17-5502.pdf