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Marion Weller-Di Marco

1 accepted papers

2024

Analyzing the Understanding of Morphologically Complex Words in Large Language Models

COLING 2024main

We empirically study the ability of a Large Language Model (gpt-3.5-turbo-instruct) to understand morphologically complex words. In our experiments, we looked at a variety of tasks to analyse German compounds with regard to compositional word formation and derivation, such as identifying the head no…

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