Triple

T16726673
Position Surface form Disambiguated ID Type / Status
Subject Blue Banana E406480 entity
Predicate passesThrough P225 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: [Blue Banana, passesThrough, Luxembourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luxembourg
Context triple: [Blue Banana, passesThrough, 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38748f538819097de1fdee9b42f34 completed April 18, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d43c49081908eca922da8f90793 completed May 10, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:20 a.m.