The creation of virtual reality simulations for training or analysis is an arduous process requiring specialized knowledge. Graphical models and even animated, articulated figures can now be obtained from websites or hired artists. Even after these assets are obtained, putting scenes together and authoring character behaviors can be a lengthy process. Furthermore, ensuring that character behaviors will be successfully performed in a virtual environment is often a trial-and-error process. Automating the creation of these behaviors and facilitating their modification by Subject Matter Experts (SMEs) – as opposed to technicians – will shorten the time required and reduce costs. This paper presents a framework (VerbsEye) for using descriptive texts, such as military operations documents to semi automate simulation creation. While previous research, such as the WordsEye system, have created static scenes from natural language inputs, our framework further automates the process and includes the generation of agent behavior scripts from the text. Specifically, we present a text-to-scene system that generates 1) scene scripts and 2) agent behavior scripts for virtual environments. The spatial information required for the scenes is obtained both explicitly through prepositions found in the input text and implicitly from the described agent behaviors. Motion data used to depict agent behaviors is exploited to provide additional spatial constraints and assure the behaviors will be possible. Automated scene creation is challenging and unlikely to result in perfection. The VerbsEye framework is evaluated in terms of how well sample military operations documents can be used to generate scenes and behaviors. The specific metrics used are the percentage of scenes and behaviors in the sample operation documents successfully processed. Our framework shows how additional automation can be used to enable SMEs and technicians to better and more quickly create training tools and environments.