Beyond source attribution: Address authorship and comparability decisions in an LLM-built scholarly knowledge graph

A knowledge graph needs a stable address for its evidence even where the literature offers competing classifications and agrees on none. Yet an address chosen for retrieval readily passes for the only classification available. This happens whenever records gathered under one name concern units that differ in boundaries, rank, or the criteria by which they are described or counted. In Sinitic dialectology the same localities recur in schemes whose units differ in membership and rank, and a unit may change its affiliation when the evidence for its diagnosis changes. Two tone counts, each quoted faithfully, may still count different things. The taxonomy of an entire field thus comes to rest on the unstable frame of a literature that contradicts itself. Neither verifying a quotation nor searching for conflicting values detects these differences. I distinguish the working address that gathers candidate evidence, the category that the source defines and the decision that admits a passage to a particular comparison, and argue that such decisions, together with the dependence among records, belong to the provenance of a comparison. On four re-runnable cases, the accompanying PaRAGraph Casebook shows where such differences arise among claims extracted by a language model and verified before entering the graph. The platform now stores the corresponding decisions as objects for one dimension of comparability, the address of a record: the placement of a locality in each source's scheme, the decision that a name in a given publication denotes a unit rather than a place, and the origin of every address. The working taxonomy can then be revised as new sources yield new claims, while the path from each comparison to its evidence stays fixed. Keywords: knowledge graphs; source attribution; classification; claim extraction; comparative concepts; Sinitic dialectology; Yue