The main purpose of the research is to understand and replicate how analysts generating a financial report by describing the trends and patterns of market indicators. While a human created report contains extensive temporal comparisons against past data, most of the current data-to-text generation models focus on describing individual tables. This work aims to enable Natural Language Generation models with temporal reasoning capability.
