The sieve-based method is flexible in incorporation of both rule-based and machine learning components. This approach extract TLinks in consecutive phases by separate model components (or sieves). Each sieve extracts TLinks, using the original input text, and the outputs from earlier sieves. TR is incorporated by taking a transitive closure after applying each sieve.