Amazon Mechanical Turk (AMT) has recently become one of the most popular crowd-sourcing platforms, allowing researchers from all over the world to create linguistic datasets quickly and at a relatively low cost. Amazon provides both a web interface and an API for AMT, but they are not very user-friendly and miss some features that can be useful for NLP researchers. In this paper, we present EasyTurk, a free tool that improves the potential of Amazon Mechanical Turk by adding to it some new features. The tool is free and released under an open source license.

EasyTurk: A User-Friendly Interface for High-Quality Linguistic Annotation with Amazon Mechanical Turk / Bocchi, Lorenzo; Frasnelli, Valentino; Palmero Aprosio, Alessio. - (2021), pp. 106-112. (Intervento presentato al convegno 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, EACL 2021 tenutosi a Online nel April 2021) [10.18653/v1/2021.eacl-demos.13].

EasyTurk: A User-Friendly Interface for High-Quality Linguistic Annotation with Amazon Mechanical Turk

Bocchi, Lorenzo;Palmero Aprosio, Alessio
2021-01-01

Abstract

Amazon Mechanical Turk (AMT) has recently become one of the most popular crowd-sourcing platforms, allowing researchers from all over the world to create linguistic datasets quickly and at a relatively low cost. Amazon provides both a web interface and an API for AMT, but they are not very user-friendly and miss some features that can be useful for NLP researchers. In this paper, we present EasyTurk, a free tool that improves the potential of Amazon Mechanical Turk by adding to it some new features. The tool is free and released under an open source license.
2021
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
Online
Association for Computational Linguistics (ACL)
978-1-954085-05-3
Bocchi, Lorenzo; Frasnelli, Valentino; Palmero Aprosio, Alessio
EasyTurk: A User-Friendly Interface for High-Quality Linguistic Annotation with Amazon Mechanical Turk / Bocchi, Lorenzo; Frasnelli, Valentino; Palmero Aprosio, Alessio. - (2021), pp. 106-112. (Intervento presentato al convegno 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, EACL 2021 tenutosi a Online nel April 2021) [10.18653/v1/2021.eacl-demos.13].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/412972
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