Abstract
We present an iterative annotation process for producing aligned, parallel corpora of abstractive and extractive summaries for narrative. Our approach uses a combination of trained annotators and crowd-sourcing, allowing us to elicit human-generated summaries and alignments quickly and at low cost. We use crowd-sourcing to annotate aligned phrases with the text-to-text generation techniques needed to transform each phrase into the other. We apply this process to a corpus of 476 personal narratives, which we make available on the Web.- Anthology ID:
- E17-2008
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Mirella Lapata, Phil Blunsom, Alexander Koller
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 46–51
- Language:
- URL:
- https://aclanthology.org/E17-2008
- DOI:
- Cite (ACL):
- Jessica Ouyang, Serina Chang, and Kathy McKeown. 2017. Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 46–51, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora (Ouyang et al., EACL 2017)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/E17-2008.pdf
- Data
- Sentence Compression