Triple

T21298871
Position Surface form Disambiguated ID Type / Status
Subject Willem de Vos E525000 entity
Predicate workLocation P7 FINISHED
Object Antwerp 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: Antwerp | Statement: [Willem de Vos, workLocation, Antwerp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antwerp
Context triple: [Willem de Vos, workLocation, Antwerp]
  • A. Antwerp chosen
    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.
  • B. Ghent
    Ghent is a small unincorporated community and ski-area destination located in Raleigh County, West Virginia, United States.
  • C. Ghent
    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.
  • D. Tervuren
    Tervuren is a municipality in Flemish Brabant, Belgium, known for its historic park, royal connections, and the Royal Museum for Central Africa.
  • E. 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.
  • 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385a24d08190bfd410c7f10fa6f7 completed April 21, 2026, 8:42 a.m.
Created at: April 16, 2026, 4:05 p.m.