Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation

April 11, 2019 ยท Declared Dead ยท ๐Ÿ› North American Chapter of the Association for Computational Linguistics

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Authors Ori Shapira, David Gabay, Yang Gao, Hadar Ronen, Ramakanth Pasunuru, Mohit Bansal, Yael Amsterdamer, Ido Dagan arXiv ID 1904.05929 Category cs.CL: Computation & Language Citations 66 Venue North American Chapter of the Association for Computational Linguistics Last Checked 4 months ago
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.
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