Abstract: This is provided a method of labelling a message or group of messages. An input is received (208) at a neural network (300, 302) including at least one recurrent layer, which may comprises LSTM memory blocks (300). The input comprising at least one word vector (xt), which represents at least one word in a message, and the at least one word vector defines a meaningful position in a word vector space. Typically the input is a sequence of word vectors corresponding to a sequence of words. The input is then processed to generate a plurality of network outputs. Each network output corresponds to a respective one of a plurality of labels. Based on the network outputs, a probability score for each of the labels is then generated (210). If it is determined (212) that at least one of the probability scores meets at least one criterion, the at least one label corresponding to the at least one probability score for which the at least one criterion is met is assigned (214) to the message.