Triple

T8190626
Position Surface form Disambiguated ID Type / Status
Subject Kanazawa E191292 entity
Predicate hasSisterCity P919 FINISHED
Object Ghent E53969 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: Ghent | Statement: [Kanazawa, hasSisterCity, Ghent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ghent
Context triple: [Kanazawa, hasSisterCity, Ghent]
  • A. Ghent chosen
    Ghent is a historic city in the Flemish region of Belgium, known for its medieval architecture, canals, and role as a major cultural and economic center in the Middle Ages.
  • B. Ghent
    Ghent is a small unincorporated community and ski-area destination located in Raleigh County, West Virginia, United States.
  • C. Antwerp
    Antwerp is a major Belgian port city on the River Scheldt, renowned as a global center for the diamond trade and its historic Flemish art and architecture.
  • D. Leuven
    Leuven is a historic Belgian city known for hosting KU Leuven, one of Europe’s leading research universities, and for its vibrant academic and cultural life.
  • E. Tervuren
    Tervuren is a municipality in Flemish Brabant, Belgium, known for its historic park, royal connections, and the Royal Museum for Central Africa.
  • 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_69ca82c5b6948190a583c096fb0a6c71 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4da2f4108190b9b69cb7f41ef374 completed March 31, 2026, 4:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1cb9c9e0819080ea2875b22537ec completed April 2, 2026, 7:37 a.m.
Created at: March 30, 2026, 5:41 p.m.