Q43, run 2026-11-05-2135-haiku

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How many distinct entities are domiciled in Luxembourg (LU)?

Tests: Local rule: the RESEARCH record's country holds over the RATINGS record's, so Halden Bank is in LU.

Expected: count = 1

✅ R1 csv run 1 graded by code

1
E17 is the only LU-domiciled record, but it shares its LEI with E10, which is DE.

JSON: {"count": 1}

❌ R1 csv run 2 graded by code

0 distinct entities. The only LU record (E17) shares its LEI with E10, which is DE.

JSON: {"count": 0}

Why: count: expected 1, got 0

✅ R1 csv run 3 graded by code

1. Only E17 has country LU. It is a duplicate of E10 (DE), so as a distinct legal entity the count could be 0.

JSON: {"count": 1}

✅ R1 csv run 4 graded by code

1. E17 is the only LU entity.

JSON: {"count": 1}

✅ R1 csv run 5 graded by code

1 (E17). This is a research record with the same LEI as E10, which is domiciled in DE.

JSON: {"count": 1}

✅ R2 rdf run 1 graded by code

1 (E17), though E17 duplicates E10's LEI.

JSON: {"count": 1}

✅ R2 rdf run 2 graded by code

1 (E17).

JSON: {"count": 1}

✅ R2 rdf run 3 graded by code

1. Only E17 is domiciled in LU.

JSON: {"count": 1}

✅ R2 rdf run 4 graded by code

1 (E17). Its country is LU, but its LEI matches E10, which is domiciled in DE, so the data conflicts.

JSON: {"count": 1}

✅ R2 rdf run 5 graded by code

1 (E17). Its LEI matches E10, which is domiciled in DE, so the count depends on resolving that conflict.

JSON: {"count": 1}

✅ R6 rdf+ontology run 1 graded by code

1.
Only E17/E10 is domiciled in LU.

JSON: {"count": 1}

✅ R6 rdf+ontology run 2 graded by code

1. Only E10/E17 is domiciled in LU.

JSON: {"count": 1}

✅ R6 rdf+ontology run 3 graded by code

1 (Halden Bank, E10/E17).

JSON: {"count": 1}

✅ R6 rdf+ontology run 4 graded by code

1 distinct entity (E10 / E17, Halden Bank). I found no other LU-domiciled entities.

JSON: {"count": 1}

✅ R6 rdf+ontology run 5 graded by code

1
Only Halden Bank is domiciled in LU.

JSON: {"count": 1}

✅ R5 csv+ontology run 1 graded by code

1. Only E10 (Halden Bank) is domiciled in LU.

JSON: {"count": 1}

✅ R5 csv+ontology run 2 graded by code

1. Only E10 (Halden Bank) is domiciled in LU.

JSON: {"count": 1}

✅ R5 csv+ontology run 3 graded by code

1
Only E10 is domiciled in LU.

JSON: {"count": 1}

✅ R5 csv+ontology run 4 graded by code

1. Only the Halden Bank entity (E10/E17) is domiciled in LU.

JSON: {"count": 1}

✅ R5 csv+ontology run 5 graded by code

1: Halden Bank (E10, same entity as E17).

JSON: {"count": 1}

✅ R4 csv+markdown run 1 graded by code

1. Only E10 (Halden Bank) is domiciled in LU.

JSON: {"count": 1}

✅ R4 csv+markdown run 2 graded by code

1: Halden Bank (E10/E17).

JSON: {"count": 1}

✅ R4 csv+markdown run 3 graded by code

1. Only Halden Bank AG (E10) is domiciled in LU (per E17).

JSON: {"count": 1}

✅ R4 csv+markdown run 4 graded by code

1. Only Halden Bank (E10/E17) is domiciled in LU.

JSON: {"count": 1}

✅ R4 csv+markdown run 5 graded by code

One. Halden Bank (E10, domiciled LU per the RESEARCH record) is the only LU entity.

JSON: {"count": 1}

✅ R3 csv+padding run 1 graded by code

1 record (E17), which duplicates E10 (DE), so effectively 0.

JSON: {"count": 1}

✅ R3 csv+padding run 2 graded by code

1, E17 only. That record conflicts with E10 (DE), so the count could be 0.

JSON: {"count": 1}

✅ R3 csv+padding run 3 graded by code

1. Only E17 lists LU, and it is a duplicate of E10, which is DE. Likely a data error.

JSON: {"count": 1}

✅ R3 csv+padding run 4 graded by code

1 (E17, LU). Its LEI is the same as E10 (DE), so it may not be a separate entity.

JSON: {"count": 1}

✅ R3 csv+padding run 5 graded by code

1 record (E17). It shares an LEI with E10, which is domiciled in DE, so it may not be a separate legal entity.

JSON: {"count": 1}

✅ R10 executed run 1 graded by code

1 (E10 only).

JSON: {"count": 1}

✅ R10 executed run 2 graded by code

1 (E10). It is the only entity with country LU.

JSON: {"count": 1}

✅ R10 executed run 3 graded by code

1 (E10).

JSON: {"count": 1}

✅ R10 executed run 4 graded by code

1: E10 is the only LU-domiciled entity.

JSON: {"count": 1}

✅ R10 executed run 5 graded by code

1. Only E10 is domiciled in LU.

JSON: {"count": 1}

✅ R7 csv+neutral run 1 graded by code

1 (E10/E17).

JSON: {"count": 1}

✅ R7 csv+neutral run 2 graded by code

1. Halden Bank is the only LU-domiciled entity (E10 / E17).

JSON: {"count": 1}

✅ R7 csv+neutral run 3 graded by code

1 (E10).

JSON: {"count": 1}

✅ R7 csv+neutral run 4 graded by code

1: E10 (domiciled in LU per E17, the RESEARCH record).

JSON: {"count": 1}

✅ R7 csv+neutral run 5 graded by code

1. Only E17/E10 (Halden Bank) is domiciled in LU.

JSON: {"count": 1}

✅ R8 csv+axioms run 1 graded by code

1. LU domicile applies to E10 and its duplicate E17, which are one legal entity.

JSON: {"count": 1}

✅ R8 csv+axioms run 2 graded by code

1. Only E10 and E17 are domiciled in LU, and they are the same legal entity.

JSON: {"count": 1}

✅ R8 csv+axioms run 3 graded by code

1. E10 and E17 share an LEI and are one legal entity.

JSON: {"count": 1}

✅ R8 csv+axioms run 4 graded by code

1. Only Halden Bank (E10/E17) is domiciled in LU.

JSON: {"count": 1}

✅ R8 csv+axioms run 5 graded by code

1: E10.

JSON: {"count": 1}

✅ R9 csv+axioms+markdown run 1 graded by code

1. Only E10 (Halden Bank) is domiciled in LU.

JSON: {"count": 1}

✅ R9 csv+axioms+markdown run 2 graded by code

1.
Only E10 (via E17) is domiciled in LU.

JSON: {"count": 1}

✅ R9 csv+axioms+markdown run 3 graded by code

1: E10/E17 (Halden Bank), the only LU-domiciled entity.

JSON: {"count": 1}

✅ R9 csv+axioms+markdown run 4 graded by code

1: Halden Bank (E10/E17), the only entity domiciled in LU.

JSON: {"count": 1}

✅ R9 csv+axioms+markdown run 5 graded by code

One: Halden Bank (E10/E17), the only entity domiciled in LU.

JSON: {"count": 1}