Triple

T10416666
Position Surface form Disambiguated ID Type / Status
Subject Aegon Asset Management E245534 entity
Predicate hasOfficeIn P1268 FINISHED
Object Luxembourg E1844 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Luxembourg | Statement: [Aegon Asset Management, hasOfficeIn, Luxembourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luxembourg
Context triple: [Aegon Asset Management, hasOfficeIn, Luxembourg]
  • A. Luxembourg chosen
    Luxembourg is a small, landlocked Western European country known for its prosperous economy, status as a major financial center, and role as a founding member of the European Union.
  • B. Luxemburg
    Luxemburg is a surname most famously associated with Rosa Luxemburg, the Marxist theorist, revolutionary socialist, and co-founder of the Spartacist League in Germany.
  • C. Lichtenstein
    Lichtenstein is a surname most famously associated with Roy Lichtenstein, the American pop artist known for his comic-strip-inspired paintings.
  • D. Lichtenstein
    Lichtenstein is a municipality in the district of Reutlingen in the German state of Baden-Württemberg, known for the nearby Lichtenstein Castle.
  • E. Belgium and Luxembourg
    Belgium and Luxembourg are neighboring Western European countries that share a close historical, economic, and cultural relationship within the Benelux union.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea108fec8190819423630888fa2b completed April 7, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69d87e6f30c88190992242b6e0c43581 completed April 10, 2026, 4:37 a.m.
Created at: April 6, 2026, 12:10 p.m.