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Introduction to Natural Language Processing, End Term

January 2025 term, 13 Apr 2025, Set QDF3

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Question 1

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Why might accuracy be a misleading metric for evaluating POS tagging systems in cases of class imbalance?

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A.
Because accuracy does not account for the number of true negatives.
B.
Because accuracy gives equal weight to all classes, even if some tags are much rarer than others.
C.
Because accuracy only measures the precision of the system, ignoring recall.
D.
Because accuracy is not affected by the number of false positives and false negatives.

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Why might accuracy be a misleading metric for evaluating POS tagging systems in cases of class imbalance? In stochastic POS tagging, why is it necessary to calculate both individual word probabilities and tag sequence probabilities? How does Retrieval-Augmented Generation (RAG) differ from standard parametric models like GPT-3?