  In this paper, we show how Quantitative Narrative Analysis and simple Natural
Language Processing techniques apply to the extraction and categorization of
data in a sample case study of the Diary of the former President of the Italian
Republic (PoR), Giorgio Napolitano. The Diary contains a record of all his
institutional meetings. This information, if properly handled, allows for an
analysis of how the PoR used his so-called soft-powers to influence the Italian
political system during his first mandate. In this paper, we propose a way to
use simple, yet very effective, Natural Language Processing techniques - such
as Regular Expressions and Named Entity Recognition - to extract information
from the Diary. Then, we propose an innovative way to organize the extracted
data relying on the methodological framework of Quantitative Narrative
Analysis. Finally, we show how to analyze the structured data under different
levels of detail using PC-ACE (Program for Computer-Assisted Coding of Events),
a software developed specifically for this task and for data visualization.
