## 3 Methodology
### BIM Query Dataset
\begin{table}
\begin{tabular}{c c c} \hline
**Index** & **BIM Query Type** & **Natural Language Query Example** \\ \hline T1 & Obtain the entire building & Display the entire building \\ T2 & Obtain components with a & Show the walls of the building \\  & single type & Show walls and concrete slabs \\ T3 & Obtain components with & within the building, excluding \\  & multiple types & other parts \\ T4 & Obtain a component with a & Locate the component within the \\  & given GUID & entire system with GUID xxx \\ T5 & Obtain components within a & Define a space: width is 5, height is \\  & specific space & 5, and depth is 5. Show all the items \\  & & in this space \\ T6 & Obtain all attributes of the & List the attributes of the component \\  & component with a given GUID & GUID xxx \\ T7 & Obtain the attributes of the same & List the attributes of all walls \\  & type of component & \\ T8 & Obtain the attribute using the given & Show the history of the walls \\ T9 & Obtain components with specific & Display walls with openings \\  & subclass components & List the floor attributes with floor \\ T10 & Obtain component properties with a & GUID xxx \\ T11 & Obtain components with given & Show load-bearing walls \\  & attribute values & Show all the components with \\  & Obtain components using class type & OmniClass value “21-07 11 13” \\ T12 & value with a given & Show all the components with \\  & classification system & OmniClass value “21-07 11 13” \\ \hline \end{tabular}
\end{table} 
Table 1: Dataset structure. selection of query needs for users and ensures the scalability and flexibility of the query language. The classification reasons are as follows:  
1. Object-Based Queries These queries focus on filtering query targets based on different component types, such as walls, floors, doors, and windows. This category includes T1, T2, T3, and T12. This classification is intuitive and aligns with real-world applications where users often need to perform precise queries for different component types (e.g., walls, floors, doors). For instance, T1 and T2 allow the retrieval of entire buildings and individual component types, respectively, while T3 can handle combined queries for multiple component types. These operations are commonly seen in practical BIM applications. 2. Component Identification or Location-Based Queries This category of queries focuses on retrieving target components through their unique identifiers (GUIDs) or spatial location ranges. It includes T4, T5, T6 and T10. Queries based on GUIDs or spatial ranges help users locate specific components or areas. For example, T4 and T5 support locating components via their GUID or spatial range, which is a common query need in architectural design and construction. Although end users typically do not directly interact with GUIDs in daily operations, GUIDs serve as unique identifiers in the BIM context, ensuring the accuracy and traceability of component queries. In practice, users often start queries based on physical or attribute information of components and later use GUIDs to pinpoint specific components for more refined queries. This method not only enhances query accuracy but also reduces computational overhead from repeated queries, enabling users to efficiently access the required information. 3. Component Attribute or Relationship-Based Queries These queries focus on filtering based on the attributes of components or their interrelationships. They are primarily used to extract detailed component information or to query the dependencies between components in the BIM model. This category includes T7, T8, T9, and T11. Attribute and relationship queries concentrate on retrieving details about the components themselves or the logical relationships between them. These types of queries are theoretically sound because in a BIM model, component attributes (such as material, size, load-bearing capacity) and component relationships (such as containment or relative positioning) are critical elements of the model.