What is the primary use of the "split the text into chunks" step?

The primary use of the "split the text into chunks" step is to make text processing manageable. When dealing with large volumes of text data, particularly in natural language processing and machine learning tasks, breaking the text into smaller, more manageable pieces allows for easier analysis and manipulation. This method helps in reducing computational load, making it easier to implement algorithms for tasks like indexing, searching, or further processing.

By chunking the text, it becomes feasible to apply various techniques, such as tokenization, which can lead to better understanding and extraction of meaning from the text, thus improving the overall efficiency and effectiveness of data processing workflows. This approach is especially useful when preparing data for training models, as it enhances the clarity and focus of the data being analyzed.