Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation. / Shapira, Ori; Gabay, David; Gao, Yang; Ronen, Hadar; Pasunuru, Ramakanth; Bansal, Mohit; Amsterdamer, Yael; Dagan, Ido.

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Vol. 1 Association for Computational Linguistics, 2019. p. 682-687.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Published
  • Ori Shapira
  • David Gabay
  • Yang Gao
  • Hadar Ronen
  • Ramakanth Pasunuru
  • Mohit Bansal
  • Yael Amsterdamer
  • Ido Dagan

Abstract

Conducting a manual evaluation is considered an essential part of summary evaluation methodology. Traditionally, the Pyramid protocol, which exhaustively compares system summaries to references, has been perceived as very reliable, providing objective scores. Yet, due to the high cost of the Pyramid method and the required expertise, researchers resorted to cheaper and less thorough manual evaluation methods, such as Responsiveness and pairwise comparison, attainable via crowdsourcing. We revisit the Pyramid approach, proposing a lightweight sampling-based version that is crowdsourcable. We analyze the performance of our method in comparison to original expert-based Pyramid evaluations, showing higher correlation relative to the common Responsiveness method. We release our crowdsourced Summary-Content-Units, along with all crowdsourcing scripts, for future evaluations.
Original languageEnglish
Title of host publicationProceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
PublisherAssociation for Computational Linguistics
Pages682-687
Number of pages6
Volume1
Publication statusPublished - Jun 2019
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

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