  The emergence of large language models (LLMs) presents an unprecedented
opportunity to automate construction contract management, reducing human errors
and saving significant time and costs. However, LLMs may produce convincing yet
inaccurate and misleading content due to a lack of domain expertise. To address
this issue, expert-driven contract knowledge can be represented in a structured
manner to constrain the automatic contract management process. This paper
introduces the Nested Contract Knowledge Graph (NCKG), a knowledge
representation approach that captures the complexity of contract knowledge
using a nested structure. It includes a nested knowledge representation
framework, a NCKG ontology built on the framework, and an implementation
method. Furthermore, we present the LLM-assisted contract review pipeline
enhanced with external knowledge in NCKG. Our pipeline achieves a promising
performance in contract risk reviewing, shedding light on the combination of
LLM and KG towards more reliable and interpretable contract management.
