Agreement is overrated: A plea for correlation to assess human evaluation reliability
Jacopo Amidei, Paul Piwek, Alistair Willis
Abstract
Open-access reader
Jacopo Amidei, Paul Piwek, Alistair Willis
Abstract
Open-access reader
Inter-Annotator Agreement (IAA) is used as a means of assessing the quality of NLG evaluation data, in particular, its reliability.According to existing scales of IAA interpretationsee, for example, Lommel et al. (2014), Liu et al. (2016), Sedoc et al. (2018) and Amidei et al. (2018a) -most data collected for NLG evaluation fail the reliability test.We confirmed this trend by analysing papers published over the last 10 years in NLG-specific conferences (in total 135 papers that included some sort of human evaluation study).Following Sampson and Babarczy (2008), Lommel et al. (2014), Joshi et al. (2016) and Amidei et al. ( 2018b), such phenomena can be explained in terms of irreducible human language variability.Using three case studies, we show the limits of considering IAA as the only criterion for checking evaluation reliability.Given human language variability, we propose that for human evaluation of NLG, correlation coefficients and agreement coefficients should be used together to obtain a better assessment of the evaluation data reliability.This is illustrated using the three case studies.
OpenAlex reports 27 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Inter-Annotator Agreement (IAA) is used as a means of assessing the quality of NLG evaluation data, in particular, its reliability.According to existing scales of IAA interpretationsee, for example, Lommel et al. (2014), Liu et al. (2016), Sedoc et al. (2018) and Amidei et al. (2018a) -most data collected for NLG evaluation fail the reliability test.We confirmed this trend by analysing papers published over the last 10 years in NLG-specific conferences (in total 135 papers that included some sort of human evaluation study).Following Sampson and Babarczy (2008), Lommel et al. (2014), Joshi et al. (2016) and Amidei et al. ( 2018b), such phenomena can be explained in terms of irreducible human language variability.Using three case studies, we show the limits of considering IAA as the only criterion for checking evaluation reliability.Given human language variability, we propose that for human evaluation of NLG, correlation coefficients and agreement coefficients should be used together to obtain a better assessment of the evaluation data reliability.This is illustrated using the three case studies.
Key concepts: Reliability (semiconductor), Plea, Computer science, Interpretation (philosophy), sort, Correlation, Agreement, Statistics