Triple

T20277345
Position Surface form Disambiguated ID Type / Status
Subject Old Town of Luxembourg City E503049 entity
Predicate hasPart P35 FINISHED
Object Clausen quarter 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: Clausen quarter | Statement: [Old Town of Luxembourg City, hasPart, Clausen quarter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clausen quarter
Context triple: [Old Town of Luxembourg City, hasPart, Clausen quarter]
  • A. Clausen chosen
    Clausen is a historic quarter of Luxembourg City known for its nightlife, old breweries, and picturesque setting along the Alzette River.
  • B. Bundsgaard
    Bundsgaard is a Danish surname most notably associated with Jacob Bundsgaard, the mayor of Aarhus, Denmark.
  • C. Viertel
    Viertel is a German-language surname borne by various notable individuals in the arts and literature.
  • D. Quarten
    Quarten is a Swiss municipality in the canton of St. Gallen, known for its location on the shores of Lake Walen and its proximity to the Flumserberg ski and hiking area.
  • E. Knudshoved
    Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
  • 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.