Getting started with cutting-edge SRL
Chapter 7, The Generative AI Revolution with ChatGPT, introduced the complexity of adapting to the widening taxonomy of deep learning models in general, and LLMs, such as ChatGPT, in particular.
SRL provides enhanced information extraction on each word’s role in a sentence. The extracted information can improve translation, summarization, and other NLP tasks. A model that understands the semantic role of words will provide better-quality NLP outputs.
However, choosing a path to implement an NLP task has become challenging. SRL is no exception. We can sum up the issues to examine with four parameters that describe the resources used in this chapter: task-specific, general-purpose, development, and self-service:
Figure 12.1: The complexity of LLM management
Figure 12.1 shows the complexity of LLM project management. The parameters interact in various possible ways for a project. The risk of each parameter must be carefully...
