7th International Conference on Technology Policy and Innovation, Monterrey Mexico, June 2003. Improving Transparency: Extracting, Visualizing, and Analyzing Corporate Relationships from SEC 10-K Documents Gabriel Lucas, Michael Gebbie, Kim Norlen and John Chuang School of Information Management and Systems University of California at Berkeley Abstract. We present a system to extract, visualize, and analyze inter-corporation relationships disclosed by public companies in their annual reports to the U.S. Securities and Exchange Commission (SEC). In improving the transparency of these disclosures, we allow policy makers, analysts, investors, and the general public to analyze these relationships at both the firm level and the industry level. Using probabilistic information retrieval and extraction techniques, we automatically extract a dataset of 45,000 relationships between 26,000 companies from over 15 gigabytes of SEC 10-K documents. These relationships range from ownerships, agreements, and personal connections to competition and legal disagreements. Information visualization and social network analytic techniques can then be applied to explore and analyze the dataset.