Benchmarking Latent Organizational Reasoning in Enterprise Systems

Summary & Methodology Analysis

The researchers introduce EntLORE, a framework that constructs a graph-grounded environment to challenge enterprise search and reasoning systems. The method functions by first reconstructing a raw graph from a combination of routine documents, authoritative organizational tables, and operational records. This raw data is processed through a versioned convention library to certify organization-specific inferences, ultimately forming a private truth graph that is projected into an anonymized document corpus. By compiling questions into executable graph programs, the framework allows for the verification of derivation and completeness without leaking the underlying truth graph to the evaluated systems. The resulting benchmark contains 2,341 documents, providing a structured way to measure performance across explicit lookup, cross-source composition, and latent organizational reasoning tasks. The evaluation involves 907 questions tested across 56 model and access configurations. A major technical finding is the persistent challenge of latent organizational reasoning. Even when systems are supplied with the correct gold-document paths, 30.4% of these latent questions remain unanswered. This failure rate stands in contrast to explicit questions (12.6% unanswered) and compositional questions (6.2% unanswered), indicating that current systems struggle to bridge the gap between retrieved documentation and implicit organizational relationships. The paper does not specify the computational overhead or inference latency required for processing these graph-grounded programs, nor does it provide details on the specific model architectures evaluated beyond the 56-configuration scope.