  Artefact descriptions are the primary carriers of engineering design
knowledge that is both an outcome and a driver of the design process. While an
artefact could be described in different connotations, the design process
requires a description to embody engineering design knowledge, which is
expressed in the text through intricate placement of entities and
relationships. As large-language models learn from all kinds of text merely as
a sequence of characters/tokens, these are yet to generate text that embodies
explicit engineering design facts. Existing ontological design theories are
less likely to guide the large-language models whose applications are currently
limited to ideation and learning purposes. In this article, we explicate
engineering design knowledge as knowledge graphs from a large sample of 33,881
patent documents. We examine the constituents of these knowledge graphs to
understand the linguistic and structural basis of engineering design knowledge.
In terms of linguistic basis, we observe that entities and relationships could
be generalised to 64 and 24 linguistic syntaxes. While relationships mainly
capture attributes ('of'), structure ('in', 'with'), purpose ('to', 'for'),
hierarchy ('include'), exemplification ('such as'), and behaviour ('to',
'from'), the hierarchical relationships could specifically be identified using
75 unique syntaxes. To understand the structural basis, we draw inspiration
from various studies on biological/ecological networks and discover motifs from
patent knowledge graphs. We identify four 3-node and four 4-node patterns that
could further be converged and simplified into sequence [->...->], aggregation
[->...<-], and hierarchy [<-...->]. Expected to guide large-language model
based design tools, we propose few regulatory precepts for concretising
abstract entities and relationships within subgraphs, while explicating
hierarchical structures.
