Algorithm 1 The ClusType algorithm
Input: biadjacency matrices {Π𝒞, ΠL, ΠR, WL, WR, Wℳ}, clustering features {Fs, Fc}, seed labels Y0, number of clusters K, parameters {α, γ, μ}
1:	Initialize {Y, C, PL, PR} with {Y0, ${\mathbf{\Pi }}_{\mathcal{C}}^T{Y}_0$, ${\mathbf{\Pi }}_L^T{Y}_0$, ${\mathbf{\Pi }}_R^T{Y}_0$}, {Uυ), V(υ), β(υ)} and U* with positive values.
2:	repeat
3:	Update candidate mention type indicator Y by Eq. (7)
4:	Update entity name type indicator C and relation phrase type signature {PL, PR} by Eq. (8)
5:	for υ = 0 to 3 do
6:	repeat
7:	Update V(υ) with Eq. (9)
8:	Normalize U(υ) = U(υ)Q(υ), V(υ) = V(υ)Q(υ)−1
9:	Update U(υ) by Eq. (10)
10:	until Eq. (11) converges
11:	end for
12:	Update consensus matrix U* and relative feature weights {β(υ)} using Eq. (12)
13:	until the objective 𝒪 in Eq. (6) converges
14:	Predict the type of mi ∈ ℳU by type(mi) = argmax Yi.