Large Language Models (LLMs), such as GPT-3.5 have shown their prowess in generating human-like text based on extensive training on vast corpora of data. Understanding ambiguity, particularly in the presence of cultural and linguistic diversity, stands as a formidable task. The same word or phrase can hold distinct meanings based on the underlying socio-linguistic context and cultural underpinnings.
Olubayo discusses the various works in Nigeria on the evaluation of the ability of Large Language Models like GPT3.5 to capture the deep contextual meaning of cultural nuances, with a view to establishing the need to address the current gaps to support the increased local usage of LLMs in health, financial inclusion, agriculture and education in emerging markets.
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