Triple

T14072237
Position Surface form Disambiguated ID Type / Status
Subject Anna Maria van Schurman E338637 entity
Predicate burialPlace P196 FINISHED
Object Wieuwerd E1077424 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: Wieuwerd | Statement: [Anna Maria van Schurman, burialPlace, Wieuwerd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wieuwerd
Context triple: [Anna Maria van Schurman, burialPlace, Wieuwerd]
  • A. Wieuwerd chosen
    Wieuwerd is a small village in the Dutch province of Friesland, historically noted as the place where the scholar Anna Maria van Schurman spent her final years.
  • B. De Wilp
    De Wilp is a village in the Dutch province of Groningen, known for its rural character and location near the border with Friesland.
  • C. Slotervaart
    Slotervaart is a residential neighborhood in the western part of Amsterdam, developed as part of the city’s post-war urban expansion.
  • D. Vader des Vaderlands
    Vader des Vaderlands is the Dutch honorific title given to William of Orange (Willem de Zwijger), revered as the founding father of the Netherlands for his leadership in the struggle for independence from Spain.
  • E. De Meent
    De Meent is a central shopping center in the Dutch town of Papendrecht, offering a variety of retail stores and services.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5c5aa828819098ef55a70a0decbc completed April 14, 2026, 3:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdefcc5708190beacccaa978a4abd completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:21 p.m.