Triple

T11968179
Position Surface form Disambiguated ID Type / Status
Subject Constant Nieuwenhuys E284845 entity
Predicate placeOfBirth P1 FINISHED
Object Amsterdam E989 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: Amsterdam | Statement: [Constant Nieuwenhuys, placeOfBirth, Amsterdam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amsterdam
Context triple: [Constant Nieuwenhuys, placeOfBirth, Amsterdam]
  • A. Amsterdam chosen
    Amsterdam is the largest city in the Netherlands, renowned as a historic commercial and cultural center characterized by its canals, trading heritage, and role as the country’s principal metropolis.
  • B. Amsterdam
    Amsterdam is a Booker Prize–winning novel by British author Ian McEwan that explores moral compromise and revenge through the intertwined lives of two old friends.
  • C. Rotterdam
    Rotterdam is a major Dutch port city known for having one of the world’s largest harbors and striking modern architecture.
  • D. Haarlem
    Haarlem is a historic Dutch city in the province of North Holland, known for its medieval architecture, cultural heritage, and role as a regional center near Amsterdam.
  • E. Osdorp
    Osdorp is a residential neighborhood in the western part of Amsterdam, Netherlands, known for its post-war urban planning and multicultural population.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9037bee54819085242a3ef3e286f9 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471a856208190bb88254090c03ed0 completed May 1, 2026, 9:26 a.m.
Created at: April 8, 2026, 9:46 p.m.