@inproceedings{91241e12a306414b97d41e503a40b8b8,
title = "CoRefi: A Crowd Sourcing Suite for Coreference Annotation",
abstract = "Coreference annotation is an important, yet expensive and time consuming, task, which often involved expert annotators trained on complex decision guidelines. To enable cheaper and more efficient annotation, we present COREFI, a web-based coreference annotation suite, oriented for crowdsourcing. Beyond the core coreference annotation tool, COREFI provides guided onboarding for the task as well as a novel algorithm for a reviewing phase. COREFI is open source and directly embeds into any website, including popular crowdsourcing platforms. COREFI Demo: aka.ms/corefi Video Tour: aka.ms/corefivideo Github Repo: https://github.com/aribornstein/corefi",
author = "Aaron Bornstein and Arie Cattan and Ido Dagan",
note = "Publisher Copyright: {\textcopyright} 2020 Association for Computational Linguistics.; 2020 System Demonstrations of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020 ; Conference date: 16-11-2020 Through 20-11-2020",
year = "2020",
language = "الإنجليزيّة",
series = "EMNLP 2020 - Conference on Empirical Methods in Natural Language Processing, Proceedings of Systems Demonstrations",
publisher = "Association for Computational Linguistics (ACL)",
pages = "205--215",
editor = "Qun Liu and David Schlangen",
booktitle = "EMNLP 2020 - Conference on Empirical Methods in Natural Language Processing, Proceedings of Systems Demonstrations",
address = "الولايات المتّحدة",
}