Computer systems and methods for identifying location entities and generating a location entity data taxonomy

At least one non-transitory computer-readable medium, wherein the at least one non-transitory computer-readable medium is provisioned with program instructions that, when executed by at least one processor, cause a computing platform to:

• obtain a two-dimensional drawing of a portion of a construction project;
• perform an image processing analysis of the two-dimensional drawing to identify one or more location entities within the two-dimensional drawing;
• derive embeddings for each location entity in the two-dimensional drawing;
• based on the derived embeddings, determine relationships between the one or more location entities;
• based on the determined relationships between the one or more location entities, generate a location entity data taxonomy that includes each identified location entity as a respective node that is related to at least one other location entity;
• cause an end-user device to display a visualization of the location entity data taxonomy;
• and
• cause the end-user device to filter the displayed visualization based on information about a given user associated with the end-user device, wherein the program instructions that are executable by the at least one processor such that the computing platform is configured to generate the location entity data taxonomy comprise program instructions that are executable by the at least one processor such that the computing platform is configured to:
• apply one or more machine-learning models that are configured to receive the derived embeddings as input and output the location entity data taxonomy.

A method carried out by a computing platform, the method comprising:

• obtaining a two-dimensional drawing of a portion of a construction project;
• performing an image processing analysis of the two-dimensional drawing to identify one or more location entities within the two-dimensional drawing;
• deriving embeddings for each location entity in the two-dimensional drawing;
• based on the derived embeddings, determining relationships between the one or more location entities;
• and
• based on the determined relationships between the one or more location entities, generating a location entity data taxonomy that includes each identified location entity as a respective node that is related to at least one other location entity, wherein generating the location entity data taxonomy comprises applying one or more machine-learning models that are configured to receive the derived embeddings as input and output the location entity data taxonomy;
• cause an end-user device to display a visualization of the location entity data taxonomy;
• and
• cause the end-user device to filter the displayed visualization based on information about a given user associated with the end-user device.