  Aims. An attempt to classify gamma-ray bursts (GRBs) with a low level of
supervision using the state-of-the-start approaches stemming from graph theory
was undertaken. Methods. Graph-based classification methods, relying on
different variants of the $k$-nearest neighbour graph, were applied to various
GRB samples in the duration-hardness ratio parameter space to infer the optimal
partitioning. Results. In most cases it is found that both two and three groups
are feasible, with the outcome being more ambiguous with an increasing sample
size. Conclusions. There is no clear indication of the presence of a third GRB
class; however, such a possibility cannot be ruled out with the employed
methodology. There are no hints at more than three classes though.
