Triple

T20277346
Position Surface form Disambiguated ID Type / Status
Subject Old Town of Luxembourg City E503049 entity
Predicate hasPart P35 FINISHED
Object Ville Haute NE NERFINISHED

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: Ville Haute | Statement: [Old Town of Luxembourg City, hasPart, Ville Haute]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ville Haute
Context triple: [Old Town of Luxembourg City, hasPart, Ville Haute]
  • A. Ville Haute chosen
    Ville Haute is the historic city-center district of Luxembourg City, known for its medieval fortifications, government buildings, and main shopping streets.
  • B. Ville Haute
    Ville Haute is the historic upper town of Bar-le-Duc, known for its old architecture and elevated position overlooking the rest of the city.
  • C. Chaumont
    Chaumont is a commune in northeastern France known as a local administrative and educational center, including hosting a campus of the University of Reims Champagne-Ardenne.
  • D. Leudeville
    Leudeville is a small commune in the Essonne department of the Île-de-France region in northern France.
  • E. Orleans
    Orleans is a coastal town on outer Cape Cod in Massachusetts known for its beaches, fishing, and role as a popular summer vacation destination.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e4cdfc81908c7cb4519a7d744b completed April 20, 2026, 6:52 p.m.
Created at: April 16, 2026, 10:35 a.m.