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Drug repositioning has been a topic of great attention to researchers and pharmaceutical companies due to its significant impact on the cost of drug discovery. There are several approaches to identify potentially novel drug candidates through repurposing. Literature mining has played a critical role in mining such information from scientific articles. In this paper, we used drug-gene and gene-disease semantic predications extracted from Medline abstracts to generate a list of potential drug-disease pairs. We further ranked the generated pairs, by assigning scores based on the predicates that qualify drug-gene and gene-disease relationships. On comparing the top-ranked drug-disease pairs against the Comparative Toxicogenomics Database (CTD), a curated database for drug-disease relations, we found that a significant percentage of top ranked pairs appeared in CTD. Co-occurrence of these high-ranked pairs in …