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Linguistic Yardsticks: Evaluating Language Technology Using Insights from Linguistic Theory

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Language technology has achieved remarkable success on practical tasks, such as machine translation and sentiment analysis, while incorporating very little theoretical linguistic knowledge. However, the appearance of success may be deceiving, because standard evaluation metrics for language technology under-represent relatively rare but linguistically interesting phenomena. Poor performance in these areas will be increasingly noticeable as technology advances and users expect more human-like behaviour. I will describe work that evaluates language technology using linguistic yardsticks: datasets designed to focus on specific phenomena, such as the semantic understanding of relative clauses, and I will consider how they may point the way toward improvements in natural language processing.

This talk is part of the Cambridge Language Sciences Annual Symposium series.

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