Triple

T2272908
Position Surface form Disambiguated ID Type / Status
Subject Jacob de Witt E50700 entity
Predicate spouse P13 FINISHED
Object Anna van den Corput E58769 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: Anna van den Corput | Statement: [Jacob de Witt, spouse, Anna van den Corput]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anna van den Corput
Context triple: [Jacob de Witt, spouse, Anna van den Corput]
  • A. Anna van den Corput chosen
    Anna van den Corput was a 17th-century Dutch woman best known as the mother of prominent Grand Pensionary and statesman Johan de Witt.
  • B. Anna van Gelder
    Anna van Gelder was the wife of famed Dutch admiral Michiel de Ruyter and a member of the Dutch bourgeoisie in the 17th century.
  • C. Anna van Egmond
    Anna van Egmond was a 16th-century Dutch noblewoman and heiress who became the first wife of William the Silent, Prince of Orange.
  • D. Coosje van Bruggen
    Coosje van Bruggen was a Dutch-American sculptor and art historian best known for her large-scale public art collaborations with her husband Claes Oldenburg.
  • E. Maria van Reigersberch
    Maria van Reigersberch was the resourceful wife of jurist Hugo Grotius, best known for orchestrating his famous escape from Loevestein Castle in a book chest.
  • 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1e872448190a1d6c6071b2a294b completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71ddc66c81909525394a8b2bb4e0 completed March 9, 2026, 7:08 a.m.
Created at: March 4, 2026, 7:48 p.m.