With the ever-increasing popularity of XML (Extensible Markup Language) as data representation and exchange on the Internet, querying XML data has become an important issue to be address. In Native XML Database (NXD), XML documents are usually modeled as trees and XML queries are typically specified in path expression. In path expression, the primitive structural relationships are Parent-Child (P-C) and Ancestor-Descendant (A-D). Thus, finding all occurrences of these relationships is crucial for XML query processing. Current methods for query processing on NXD usually employ either sequential traversing of tree-structured model or a decomposition-matching-merging processes. We adopt the later approach and propose a novel hybrid query optimization technique, INLAB comprising both indexing and labeling technologies. Furthermore, we also propose several algorithms to create INLAB encoding and analyze the path query. The authors implemented their technique and present performance results over several benchmarking datasets, which prove the viability of their approach.