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Real-time On-Demand Crowd-powered Entity Extraction

About

Output-agreement mechanisms such as ESP Game have been widely used in human computation to obtain reliable human-generated labels. In this paper, we argue that a "time-limited" output-agreement mechanism can be used to create a fast and robust crowd-powered component in interactive systems, particularly dialogue systems, to extract key information from user utterances on the fly. Our experiments on Amazon Mechanical Turk using the Airline Travel Information System (ATIS) dataset showed that the proposed approach achieves high-quality results with an average response time shorter than 9 seconds.

Ting-Hao 'Kenneth' Huang, Yun-Nung Chen, Jeffrey P. Bigham• 2017

Related benchmarks

TaskDatasetResultRank
Entity extractionATIS Class D (context-dependent)
Precision81.4
3
Entity extractionATIS (unevaluable) (Class X)
Precision65.4
3
Entity extractionATIS Class A (context-independent)
Precision86.7
3
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