In order to do that, they started by automatically creating training data using the cataphora-like shell noun constructions from Table 3 in Section 3.1.2 and extracting the shell content using syntactic information.
they extracted instances following seven cataphora-like patterns: N-be-to, N-be-that, N-be-wh, N-to, N-that, N-wh, and N-of, and one anaphora-like pattern, Sub-be-N. Later, Kolhatkar and Hirst (2014) observed that simply using lexico-syntactic patterns creates noisy data.