The graph search components of the system operate solely on the basis of database and ontology identifiers, but it is necessary to allow users to query the graph using natural language strings such as p53 and cancer. To implement this feature, we analyze the grounded annotations to determine the identifiers commonly associated with each string in text. This evidence concerns the gene TP53 and cancer.