Probabilistic graphical models like Markov Logic networks (Richardson & Domingos, 2006;Domingos et al., 2007;Domingos & Lowd, 2009) or factor graphs (Loeliger, 2008;Koller & Friedman, 2009) take into consideration constraints such as transitivity, while spectral clustering methods (Luxburg, 2007) implicitly consider transitivity in the underlying eigenspace decomposition, but suffer from high computational complexity.
this is also done for the cooccurring mention groups, leading to the extended scope of the original mention group considered.