Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora

Jessica Ouyang, Serina Chang, Kathy McKeown


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:
Bibkey:
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)
Copy Citation:
PDF:
https://aclanthology.org/E17-2008.pdf
Data
Sentence Compression