Paper: Crowdsourcing the evaluation of a domain-adapted named entity recognition system

ACL ID N10-1051
Title Crowdsourcing the evaluation of a domain-adapted named entity recognition system
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

Named entity recognition systems sometimes have difficulty when applied to data from do- mains that do not closely match the training data. We first use a simple rule-based tech- nique for domain adaptation. Data for robust validation of the technique is then generated, and we use crowdsourcing techniques to show that this strategy produces reliable results even on data not seen by the rule designers. We show that it is possible to extract large im- provements on the target data rapidly at low cost using these techniques.