Generating Summaries of Line Graphs

This demo presents a Natural Language Gener-ation (NLG) system that generates summaries of informational graphics, specifically simple line graphs, present in popular media. The sys-tem is intended to capture the high-level knowledge conveyed by the graphic and its out-standing visual features. It comprises a content selection phase that extracts the most important content of the graphic, an organization phase, which orders the propositions in a coherent manner, and a realization phase that uses the text surrounding the article to make decisions on the choice of lexical items and amount of ag-gregation applied to the propositions to gener-ate the summary of the graphic.