Current approaches to automatic, class specii??c, image retrieval from the World Wide Web (WWW) by linguistic query often make use of an imagea??s internal characteristics and i??le meta-data to augment and improve result accuracy. We propose that, in extension, improvement can be achieved in relevance, noise-reduction and completeness through sense disambiguation and contextual meta-data prepossessing. Our schemes exploits a linguistic ontology identifying query relevant homographs used to construct sense specii??c keyword sets allowing for enhanced image search and result ranking via the calculation of relatedness between query homographs and image context prior to any additional i??ltering. Within the paper we investigate different schemes for keyword set construction; ontology exclusive and authority extended, along with three differing ranking mechanisms.