In this paper we present preliminary results for a pattern-based approach to parse web-based queries. The approach is designed to identify and categorize queries that include a geographical reference. Due to the ungrammaticality, multilinguality and ambiguity of the language in the 800,000 web-based queries in the collection, we started by building a list of all the different words in the queries, similar to creating an index. Next, a lookup of the words was done in a list of countries to identify potential locations. Because many locations were missed, we further analyzed the queries looking for spatial prepositions and syntactic cues. Queries were processed by combining search in gazetteers with a set of patterns. Categorization was also based on patterns. Results were low in terms of recall and precision mainly because the set of patterns is incomplete. Further statistical analysis and application of machine learning techniques is likely to improve performance. Error analysis of the results is discussed in detail.