Triple

T15478739
Position Surface form Disambiguated ID Type / Status
Subject Royal Military Medical Academy in Utrecht E376856 entity
Predicate notableStudent P4838 FINISHED
Object Christiaan Eijkman E77873 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: Christiaan Eijkman | Statement: [Royal Military Medical Academy in Utrecht, notableStudent, Christiaan Eijkman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christiaan Eijkman
Context triple: [Royal Military Medical Academy in Utrecht, notableStudent, Christiaan Eijkman]
  • A. Christiaan Eijkman chosen
    Christiaan Eijkman was a Dutch physician and Nobel Prize–winning physiologist whose work on beriberi helped establish the concept of vitamins as essential dietary factors.
  • B. Andries Bonger
    Andries Bonger was a Dutch art collector and dealer closely connected to the Van Gogh family and the early promotion of Vincent van Gogh’s work.
  • C. Martinus Beijerinck
    Martinus Beijerinck was a pioneering Dutch microbiologist and botanist whose work helped establish virology and modern microbiology.
  • D. Gerrit Jan Gorter
    Gerrit Jan Gorter is a Dutch local politician who serves as the mayor of the municipality of Zeewolde in the Netherlands.
  • E. Frits van der Meer
    Frits van der Meer is a notable individual, likely recognized for significant contributions in his professional or public field.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f8a77a081909f12f13660452f4a completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d4661088190bb53161247effcc4 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 3:34 a.m.