Perhaps because its technical intricacies are so difficult to grasp for the lay-person, natural language processing (NLP) scholarship borrows some of its terminology from other fields: “signals”, “noise”, “gold standards” and “ground-truthing” to name but a few. Used to describe the process of evaluating results in NLP, the term “ground-truthing” implies something of its other meanings – a sort of reality check that what is being measured remotely is actually true – but does it do this in practice?

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