Evaluating a Token Classification System
A text-processing system uses two components: a 'generator' that alters an original sentence, and a 'discriminator' that then labels each word in the altered sentence as either 'original' or 'replaced'. The discriminator's goal is to identify which words in the final sentence are different from the original words at the same position.
Review the following process and outcome. Based on the described goal of the discriminator, is its final label for the word 'jumps' correct? Justify your answer.
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models
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A text-processing system is designed to identify altered words in a sentence. It uses a 'generator' to produce a new version of an original sentence, and then a 'discriminator' to label each word in the new sentence as either 'original' (if it's the same as the word in the original sentence) or 'replaced' (if the generator changed it).
Original Sentence: "The scientist discovered a new planet." Generator's Output Sentence: "The scientist found a new planet."
Based on its task, how should the discriminator label the words 'found' and 'planet' in the generator's output sentence?
Discriminator Labeling Logic
Evaluating a Token Classification System