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Creation of machine-usable, high-quality knowledge-bases is a critical prerequisite for many important applications that rely on availability of high-level of autonomous decision-making and reasoning capabilities. Manual construction of knowledge-bases for complex applications is a time-consuming and expensive process. In such application domains, however, a vast amount of knowledge is available in human-readable format, and it could be leveraged to build knowledge-bases automatically. Natural Language Processing (NLP)-based techniques provide an attractive option for this process. The field of NLP has made rapid strides in last several years and resulted in increased usage across a variety of consumer-facing applications. However, their usage for knowledge-base construction in the aviation industry remains rather limited to date. We present our assessment of using various NLP-based tools for the creation of aviation-focused, high-quality, machineprocessable, and human-legible knowledge bases (KBs) for various applications. We identify several gaps, both at the application and fundamental levels, and also identify potential directions for future research that could help overcome the challenges.