The task of Named Entity Disambiguation is to map entity mentions in the document to their correct entries in some knowledge base. We present a novel graph-based disambiguation approach based on Personalized PageRank (PPR) that combines local and global evidence for disambiguation and effectively filters out noise introduced by in- correct candidates. Experiments show that our method outperforms state-of-the-art ap- proaches by achieving 91.7% in micro- and 89.9% in macroaccuracy on a dataset of 27.8K named entity mentions.