Efficient evaluation of queries on XML data is a major research issue. Structural join based techniques are well known for XPath evaluation. For the long path expressions, join techniques are not efficient as they increase the number of joins and disk I/O cost. Path based techniques try to reduce the number of joins. In this paper, we propose a metadata guided query evaluation technique which uses path based storage. We use interval encoding for the nodes. In addition, we use Strong DataGuide to assign integer path labels to distinct root-to-node label paths in the data tree. An element list is maintained for each distinct path consisting of nodes that can be reached by that path. The Element-Map gives the one-to-many mapping between element names (or tag names) to element lists with nodes having that tag-name. The Path-Map gives the root-to-leaf path for a given path label. Using these structures, we can combine top-down path matching and bottom-up path selections to efficiently evaluate linear path expressions. For twig queries, we perform structural joins at branch points. Through experimental evaluation on standard datasets, we show that our approach outperforms the existing path-index based approaches which in turn outperform structural join methods.