Extracting and organizing information about events requires pre-specification of templates or schemas. This project aims to automatically discover the key entities and their roles by analyzing large volumes of news articles. Our previous work developed a semantic resource called Rel-grams, a relational analogue to lexical n-grams. Rel-grams capture co-occurrence between relations expressed in text, which can be used to automatically generate schemas [EMNLP 2013, AKBC-WEKEX 2012].