Praveen Paritosh

Also published as: Praveen P


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Cross-replication Reliability - An Empirical Approach to Interpreting Inter-rater Reliability
Ka Wong | Praveen Paritosh | Lora Aroyo
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

When collecting annotations and labeled data from humans, a standard practice is to use inter-rater reliability (IRR) as a measure of data goodness (Hallgren, 2012). Metrics such as Krippendorff’s alpha or Cohen’s kappa are typically required to be above a threshold of 0.6 (Landis and Koch, 1977). These absolute thresholds are unreasonable for crowdsourced data from annotators with high cultural and training variances, especially on subjective topics. We present a new alternative to interpreting IRR that is more empirical and contextualized. It is based upon benchmarking IRR against baseline measures in a replication, one of which is a novel cross-replication reliability (xRR) measure based on Cohen’s (1960) kappa. We call this approach the xRR framework. We opensource a replication dataset of 4 million human judgements of facial expressions and analyze it with the proposed framework. We argue this framework can be used to measure the quality of crowdsourced datasets.


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Scaling Semantic Frame Annotation
Nancy Chang | Praveen Paritosh | David Huynh | Collin F. Baker
Proceedings of The 9th Linguistic Annotation Workshop


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Hybrid Named Entity Recognition System for South and South East Asian Languages
Praveen P | Ravi Kiran V
Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages