Triple

T15758708
Position Surface form Disambiguated ID Type / Status
Subject Arrondissement of Ghent E382036 entity
Predicate contains P35 FINISHED
Object Gavere E248431 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: Gavere | Statement: [Arrondissement of Ghent, contains, Gavere]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gavere
Context triple: [Arrondissement of Ghent, contains, Gavere]
  • A. Gavere chosen
    Gavere is a municipality in the Belgian province of East Flanders, known for its rural character and several constituent villages.
  • B. Gavere-Semmerzake
    Gavere-Semmerzake is a Belgian military air base used by the Belgian Air Force.
  • C. Veurne
    Veurne is a historic town in western Belgium known for its well-preserved medieval center and Flemish Renaissance architecture.
  • D. Zierikzee
    Zierikzee is a historic Dutch town on the island of Schouwen-Duiveland in Zeeland, known for its well-preserved medieval center and maritime heritage.
  • E. Merelbeke
    Merelbeke is a municipality in East Flanders, Belgium, known in part for hosting Ghent University's Faculty of Veterinary Medicine.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b35ea48190a758ee76a57b5451 completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69fffee4f84c81908b2c7e216ef159e0 completed May 10, 2026, 3:43 a.m.
Created at: April 10, 2026, 4:47 a.m.