Filings through 2026-08-31 — 16,172 rows

README.md

@@ -16,8 +16,8 @@ size_categories:
 # 10-K Supply-Chain Graph
 
 Customer and supplier relationships that US-listed companies name **in their own
-SEC 10-K filings**, extracted into a directed graph. **17,039 rows
-across 2,753 filers**, of which 3,588
+SEC 10-K filings**, extracted into a directed graph. **16,172 rows
+across 2,659 filers**, of which 3,568
 resolve to a counterparty we also cover.
 
 Every row carries the accession number of the filing it came from, so any single
@@ -77,14 +77,14 @@ edges[(edges.source_ticker == "NVDA") & (edges.relation_type == "supplier")]
   ticker — Hon Hai resolves to `2317`, its code on the Taiwan exchange — so
   joining it against a US-only security master will silently drop rows rather
   than fail.
-- **`related_name` is verbatim, and not normalised.** 12,377
-  distinct strings appear across 17,039 rows, so one company can
+- **`related_name` is verbatim, and not normalised.** 11,623
+  distinct strings appear across 16,172 rows, so one company can
   show up under several spellings ("Walmart", "Walmart Inc.", "Walmart, Inc.").
   That is deliberate — the string is what the filing said, and normalising it in
   place would break the audit trail back to the source document. Entity
   resolution beyond `related_ticker` is yours to do.
-- **The history is thin, and the date range flatters it.** 16,741
-  of the 17,039 rows come from filings in the last
+- **The history is thin, and the date range flatters it.** 15,888
+  of the 16,172 rows come from filings in the last
   2 years. Earlier filings are in here and reach back much
   further, but they are a tail, not a panel: this is a current-state graph with
   some history, not a time series you can difference.