Q43, run 2026-11-05-1233-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. Only E17 lists LU. However, E17 shares an LEI with E10, which is DE, so it may be the same entity.

JSON: {"count": 1}

✅ R1 csv run 2 graded by code

1: E17 only. This counts the conflicting LU record, so it's the same legal entity as E10, which is coded DE.

JSON: {"count": 1}

✅ R1 csv run 3 graded by code

1. Only E17 is recorded as LU, but its LEI matches E10, which is recorded as DE. If the two are the same entity, the count is 0.

JSON: {"count": 1}

✅ R1 csv run 4 graded by code

1 (E17). This is based on the record alone. E17 shares its LEI with E10, so it may not be a separate entity.

JSON: {"count": 1}

✅ R1 csv run 5 graded by code

1. Only E17 has LU as its country. It shares its LEI with E10, which is DE, so the count could be 0.

JSON: {"count": 1}

✅ R2 rdf run 1 graded by code

1: E17, the only entity domiciled in LU.

JSON: {"count": 1}

✅ R2 rdf run 2 graded by code

1 (E17, LU). That record shares E10's LEI, so it may be the same legal entity as E10 (DE), in which case the count would be 0.

JSON: {"count": 1}

✅ R2 rdf run 3 graded by code

1
Only E17 is domiciled in Luxembourg, but its LEI matches E10, which is in DE.

JSON: {"count": 1}

✅ R2 rdf run 4 graded by code

1. E17 is the only LU entity.

JSON: {"count": 1}

✅ R2 rdf run 5 graded by code

1: E17, per its LU record. That record conflicts with E10's DE.

JSON: {"count": 1}

✅ R6 rdf+ontology run 1 graded by code

1: E10/E17, Halden Bank.

JSON: {"count": 1}

✅ R6 rdf+ontology run 2 graded by code

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

JSON: {"count": 1}

✅ R6 rdf+ontology run 3 graded by code

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

JSON: {"count": 1}

✅ R6 rdf+ontology run 4 graded by code

**1.** The only LU entity is E10 (Halden Bank), with E17 as its duplicate.

JSON: {"count": 1}

✅ R6 rdf+ontology run 5 graded by code

1
Only Halden Bank (E10, same entity as E17) is domiciled in LU.

JSON: {"count": 1}

✅ R5 csv+ontology run 1 graded by code

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

JSON: {"count": 1}

✅ R5 csv+ontology run 2 graded by code

1. Only E10 (Halden Bank, via E17) is domiciled in Luxembourg.

JSON: {"count": 1}

✅ R5 csv+ontology run 3 graded by code

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

JSON: {"count": 1}

✅ R5 csv+ontology run 4 graded by code

1. Halden Bank (E10/E17) is the only entity domiciled in Luxembourg.

JSON: {"count": 1}

✅ R5 csv+ontology run 5 graded by code

1. Only Halden Bank AG (E10/E17).

JSON: {"count": 1}

✅ R4 csv+markdown run 1 graded by code

1. Only E10 (E17 is the same entity) is domiciled in LU.

JSON: {"count": 1}

✅ R4 csv+markdown run 2 graded by code

1. Only E10 (Halden Bank) is domiciled in LU, per the RESEARCH record.

JSON: {"count": 1}

✅ R4 csv+markdown run 3 graded by code

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

JSON: {"count": 1}

✅ R4 csv+markdown run 4 graded by code

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

JSON: {"count": 1}

✅ R4 csv+markdown run 5 graded by code

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

JSON: {"count": 1}

✅ R3 csv+padding run 1 graded by code

1 record (E17). It is the same LEI as E10, which is recorded as DE, so the data conflicts.

JSON: {"count": 1}

✅ R3 csv+padding run 2 graded by code

1 record (E17), but it shares E10's LEI, which is domiciled in DE, so this is likely a data error.

JSON: {"count": 1}

✅ R3 csv+padding run 3 graded by code

1. E17 is the only record domiciled in LU. Its LEI matches E10, which is DE, so this count is contested.

JSON: {"count": 1}

✅ R3 csv+padding run 4 graded by code

1: E17 only. Its LEI matches E10, which is DE-domiciled, so the LU record may be a duplicate.

JSON: {"count": 1}

✅ R3 csv+padding run 5 graded by code

1 record (E17), but E17 shares its LEI with E10, which is DE-domiciled. So the true count of LU-domiciled entities could be 0.

JSON: {"count": 1}

✅ R10 executed run 1 graded by code

1. E10 is the only entity with country LU.

JSON: {"count": 1}

✅ R10 executed run 2 graded by code

1. Only E10 is domiciled in LU.

JSON: {"count": 1}

✅ R10 executed run 3 graded by code

1. Only E10 is domiciled in LU.

JSON: {"count": 1}

✅ R10 executed run 4 graded by code

1. Only E10 is domiciled in LU.

JSON: {"count": 1}

✅ R10 executed run 5 graded by code

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

JSON: {"count": 1}

✅ R7 csv+neutral run 1 graded by code

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

JSON: {"count": 1}

✅ R7 csv+neutral run 2 graded by code

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

JSON: {"count": 1}

✅ R7 csv+neutral run 3 graded by code

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

JSON: {"count": 1}

✅ R7 csv+neutral run 4 graded by code

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

JSON: {"count": 1}

✅ R7 csv+neutral run 5 graded by code

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

JSON: {"count": 1}

✅ R8 csv+axioms run 1 graded by code

1. Only E10 (merged with E17) is domiciled in LU.

JSON: {"count": 1}

✅ R8 csv+axioms run 2 graded by code

1. The only entity domiciled in LU is Halden Bank, which is E10 and E17.

JSON: {"count": 1}

✅ R8 csv+axioms run 3 graded by code

1. Only E10 (Halden Bank, which includes E17) is domiciled in LU.

JSON: {"count": 1}

✅ R8 csv+axioms run 4 graded by code

1. Only E10 (which includes E17) is domiciled in LU.

JSON: {"count": 1}

✅ R8 csv+axioms run 5 graded by code

1
Only E10/E17 (one legal entity) is domiciled in LU.

JSON: {"count": 1}

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

1. Only Halden Bank (E10, with E17) is domiciled in Luxembourg.

JSON: {"count": 1}

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

1. Only Halden Bank (E10, which is also E17) is domiciled in LU.

JSON: {"count": 1}

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

1: E10, since E17 is the same entity.

JSON: {"count": 1}

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

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

JSON: {"count": 1}

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

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

JSON: {"count": 1}