Crowd-Sourced Iterative Annotation for Narrative Summarization Corpora

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.

• Publication year

  2017

• Venue

  Conference of the European Chapter of the Association for Computational Linguistics

• Publication date

  2017-04-01

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.18653/V1/E17-2008
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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