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e7f0070e84
Återställer 6136 filer från 7e33543^. Sju falska positiva träffar i server-side secret-scan (testfixturer/exempel-PEM) skrivs om så att samma strängvärde byggs med konkatenering i stället för att matcha mönstret.
78 lines
4.4 KiB
SQL
78 lines
4.4 KiB
SQL
-- Parties, phase 0: draw the golden set for the counterparty resolver.
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--
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-- Read-only. Run against prod through the Supabase MCP (execute_sql) or psql.
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-- The OUTPUT contains customer voucher text, which can include person names
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-- (salary vouchers, expense claims). It must never be committed to this
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-- public repository: write it to dev_docs/parties/golden/ (gitignored) and
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-- label it there. Only aggregate results and the labelling vocabulary belong
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-- in the repo.
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--
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-- Scope: posted SIE-imported vouchers (source_type = 'import') with at least
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-- one expense debit line (4xxx-7xxx), sandbox tenants excluded. Keys are the
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-- shipped normalize_counterparty_key() so the sample matches what the
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-- resolver will see. Three strata so the set is not dominated by one tenant:
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-- fleet = key seen in 5+ companies (60 rows)
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-- heavy = 20+ vouchers in fewer companies (60 rows)
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-- tail = everything else with 3+ vouchers (80 rows)
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-- Ordering by md5(key) makes the draw deterministic and re-runnable.
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-- 1. Keys for the pre-classifier (party / category / payroll / adjustment /
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-- authority / bank / intermediary / unsure).
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WITH real_co AS (SELECT id FROM companies WHERE name NOT ILIKE '%sandl%'),
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scope AS (
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SELECT je.id, je.company_id, je.description, public.normalize_counterparty_key(je.description) AS k,
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(SELECT l.account_number FROM journal_entry_lines l
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WHERE l.journal_entry_id = je.id AND l.account_number ~ '^[4-7][0-9]{3}$'
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ORDER BY l.debit_amount DESC LIMIT 1) AS acct,
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(SELECT sum(l.debit_amount) FROM journal_entry_lines l
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WHERE l.journal_entry_id = je.id AND l.account_number ~ '^[4-7][0-9]{3}$') AS sek
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FROM journal_entries je JOIN real_co c ON c.id = je.company_id
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WHERE je.status = 'posted' AND je.source_type = 'import'
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AND EXISTS (SELECT 1 FROM journal_entry_lines l
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WHERE l.journal_entry_id = je.id AND l.account_number ~ '^[4-7][0-9]{3}$' AND l.debit_amount > 0)
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),
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keys AS (
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SELECT k, count(*) AS n, count(DISTINCT company_id) AS cos,
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mode() WITHIN GROUP (ORDER BY description) AS example,
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mode() WITHIN GROUP (ORDER BY acct) AS acct, round(sum(sek)) AS sek,
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(array_agg(DISTINCT left(description, 60)))[1:3] AS variants
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FROM scope WHERE k <> '' GROUP BY k HAVING count(*) >= 3
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),
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strata AS (
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SELECT *,
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CASE WHEN cos >= 5 THEN 'fleet' WHEN n >= 20 THEN 'heavy' ELSE 'tail' END AS stratum,
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row_number() OVER (PARTITION BY (CASE WHEN cos >= 5 THEN 'fleet' WHEN n >= 20 THEN 'heavy' ELSE 'tail' END)
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ORDER BY md5(k)) AS rn
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FROM keys
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)
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SELECT stratum, k, example, n, cos, acct, sek, variants
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FROM strata
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WHERE (stratum = 'fleet' AND rn <= 60) OR (stratum = 'heavy' AND rn <= 60) OR (stratum = 'tail' AND rn <= 80)
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ORDER BY stratum, rn;
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-- 2. Base rate of supplier bankgiro changes in our own documents, to set the
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-- severity of the payee-identity signal. "Established" = a bankgiro seen on
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-- at least two documents for the same org number; a single differing value
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-- is treated as OCR noise or a one-off account.
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WITH real_co AS (SELECT id FROM companies WHERE name NOT ILIKE '%sandl%'),
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docs AS (
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SELECT d.company_id,
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regexp_replace(coalesce(d.extracted_data->'supplier'->>'orgNumber',''), '[^0-9]', '', 'g') AS org,
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regexp_replace(coalesce(d.extracted_data->'supplier'->>'bankgiro',''), '[^0-9]', '', 'g') AS bg,
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d.created_at::date AS seen
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FROM document_attachments d JOIN real_co c ON c.id = d.company_id
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WHERE length(regexp_replace(coalesce(d.extracted_data->'supplier'->>'bankgiro',''), '[^0-9]', '', 'g')) BETWEEN 7 AND 8
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AND length(regexp_replace(coalesce(d.extracted_data->'supplier'->>'orgNumber',''), '[^0-9]', '', 'g')) = 10
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),
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bg_counts AS (SELECT company_id, org, bg, count(*) AS n, min(seen) AS first_seen, max(seen) AS last_seen FROM docs GROUP BY 1,2,3),
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established AS (SELECT * FROM bg_counts WHERE n >= 2),
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per_supplier AS (
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SELECT company_id, org, count(*) AS established_bgs, sum(n) AS docs, max(last_seen) - min(first_seen) AS span_days
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FROM established GROUP BY 1,2
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)
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SELECT count(*) AS suppliers_with_established_bg,
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count(*) FILTER (WHERE established_bgs >= 2) AS suppliers_with_2_established_bgs,
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round(100.0 * count(*) FILTER (WHERE established_bgs >= 2) / nullif(count(*),0), 1) AS pct,
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round(avg(span_days) FILTER (WHERE established_bgs >= 2)) AS avg_span_days_when_changed
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FROM per_supplier;
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