  The "Information Retrieval in Software Engineering (IRSE)" at FIRE 2023
shared task introduces code comment classification, a challenging task that
pairs a code snippet with a comment that should be evaluated as either useful
or not useful to the understanding of the relevant code. We answer the code
comment classification shared task challenge by providing a two-fold
evaluation: from an algorithmic perspective, we compare the performance of
classical machine learning systems and complement our evaluations from a
data-driven perspective by generating additional data with the help of large
language model (LLM) prompting to measure the potential increase in
performance. Our best model, which took second place in the shared task, is a
Neural Network with a Macro-F1 score of 88.401% on the provided seed data and a
1.5% overall increase in performance on the data generated by the LLM.
