What is meant by entities trained from scratch?

Entities trained from scratch refer to those that are developed entirely through the efforts and input of users, utilizing machine learning techniques. This means that the users design and train the model without relying on pre-defined or pre-trained entities. It allows for customization and specificity according to particular use cases or datasets that the users are working with, leading to more accurate and relevant outcomes in tasks such as natural language processing or data extraction.

This choice highlights the emphasis on the hands-on involvement of users in creating entities tailored to their specific needs, distinguishing them from entities that may be generated automatically or those that benefit from statistical data alone. The notion here is that the training process is comprehensive and built from the ground up, enabling more nuanced and adaptable AI solutions based on particular requirements.