Which linguistic breakthrough most significantly improved retail chatbots' ability to understand customer queries in the late 2010s?

In the intersection of linguistics and retail technology, chatbots have transformed customer service experiences. They've evolved from simple rule-based systems to sophisticated AI-powered assistants that understand context, nuance, and multiple languages. This poll tests your knowledge about the development of retail chatbot technology and its linguistic foundations.

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BERT (Bidirectional Encoder Representations from Transformers), which allowed chatbots to understand context and word relationships
Simple keyword matching algorithms that identify product names in customer requests
Phonological pattern recognition that improved voice-to-text accuracy
Multilingual translation matrices that allowed chatbots to operate in multiple languages simultaneously