Improving the Annotation of Sentence Specificity
Junyi Jessy Li, Bridget O’Daniel, Yi Wu, Wenli Zhao, Ani Nenkova
Abstract
We introduce improved guidelines for annotation of sentence specificity, addressing the issues encountered in prior work. Our annotation provides judgements of sentences in context. Rather than binary judgements, we introduce a specificity scale which accommodates nuanced judgements. Our augmented annotation procedure also allows us to define where in the discourse context the lack of specificity can be resolved. In addition, the cause of the underspecification is annotated in the form of free text questions. We present results from a pilot annotation with this new scheme and demonstrate good inter-annotator agreement. We found that the lack of specificity distributes evenly among immediate prior context, long distance prior context and no prior context. We find that missing details that are not resolved in the the prior context are more likely to trigger questions about the reason behind events, “why” and “how”. Our data is accessible at http://www.cis.upenn.edu/~nlp/corpora/lrec16spec.html- Anthology ID:
- L16-1620
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 3921–3927
- Language:
- URL:
- https://aclanthology.org/L16-1620
- DOI:
- Cite (ACL):
- Junyi Jessy Li, Bridget O’Daniel, Yi Wu, Wenli Zhao, and Ani Nenkova. 2016. Improving the Annotation of Sentence Specificity. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 3921–3927, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Improving the Annotation of Sentence Specificity (Li et al., LREC 2016)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/L16-1620.pdf