Triple

T4172871
Position Surface form Disambiguated ID Type / Status
Subject Luxemburg E86404 entity
Predicate hasVariant P455 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: [Luxemburg, hasVariant, Luxembourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luxembourg
Context triple: [Luxemburg, hasVariant, 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. Belgium and Luxembourg
    Belgium and Luxembourg are neighboring Western European countries that share a close historical, economic, and cultural relationship within the Benelux union.
  • E. Liechtenstein
    Liechtenstein is a small, landlocked principality in Central Europe known for its alpine landscape, strong financial sector, and status as one of the world's wealthiest countries per capita.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02e65b548190be095df62091b960 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a84713f88190a051b7d94b89d585 completed March 14, 2026, 6:26 p.m.
Created at: March 9, 2026, 3:45 p.m.