Two teams are developing systems to simplify complex sentences.

• Team Alpha builds their system with separate, specialized modules: one for replacing difficult words with simpler synonyms, another for splitting long sentences, and a third for reordering phrases to improve readability. Each module is developed and tuned independently.
• Team Beta uses a single, large neural network. They train it on a vast dataset of complex sentences and their corresponding human-written simplifications, allowing the model to learn the entire simplification process from the data directly.

A test sentence requires both a difficult word to be replaced and a significant change in sentence structure to be made simpler. Which team's system is better equipped to handle this type of complex, multi-faceted simplification, and why?