In order for automated navigation systems to operate effectively, the route instructions they produce must be clear, concise and easily understood by users. Thequality and coherence of route instructions may be improved via landmark chunking, whereby a turning instruction is given with reference to a nearby landmark. In order to incorporate a landmark within a coherent sentence, it is necessary to first understand how that landmark is conceptualised by travellers — whether it is perceived as point-like, line-like or area-like. This conceptualisation determines which prepositions and verbs are appropriate when referring to the landmark. This thesis investigates the viability of automatically classifying the conceptualisation of landmarks relative to a given city context. First, we construct a web-based annotation interface to solicit gold-standard judgements from expert annotators over a set of landmarks for three major cities (Melbourne, Hamburg and Tokyo). We then experiment with the use of web data to learn the default conceptualisation of those landmarks, analysing their occurrence in a fixed set of lexico-syntactic patterns. Based on this, we develop two automated landmark classifiers and evaluate them against the gold standard annotations,investigating patterns of convergence or divergence in landmark categorisation.