Triple

T11373996
Position Surface form Disambiguated ID Type / Status
Subject Apeldoorn E269415 entity
Predicate hasTwinTown 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: [Apeldoorn, hasTwinTown, Ghent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ghent
Context triple: [Apeldoorn, hasTwinTown, 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_69d6aacca1048190b39dbbc2174616fa completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea8d244c8190b865260338edb532 completed April 9, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58bdaabd48190ab533c1c7f3b5fd8 completed April 20, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:33 p.m.