Imagine two language models, Model A and Model B. Model A is trained on a massive dataset of English sentences and can accurately complete or paraphrase sentences it has seen before. However, it struggles significantly with sentences that use familiar words in new grammatical structures. Model B, while trained on a smaller dataset, can successfully interpret and generate sentences with novel combinations of words and structures it has never encountered. Analyze the fundamental difference in the learning capabilities of these two models. What specific ability does Model B possess that Model A lacks, and why is this ability crucial for achieving true language understanding?