Triple

T1414366
Position Surface form Disambiguated ID Type / Status
Subject Anna Cornelia Carbentus E31878 entity
Predicate residence P75 FINISHED
Object Nuenen E280743 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: Nuenen | Statement: [Anna Cornelia Carbentus, residence, Nuenen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nuenen
Context triple: [Anna Cornelia Carbentus, residence, Nuenen]
  • A. Nuenen chosen
    Nuenen is a village in the southern Netherlands, known for its association with both the painter Vincent van Gogh and computer scientist Edsger W. Dijkstra.
  • B. Schoonhoven
    Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
  • C. Leiderdorp
    Leiderdorp is a town and municipality in the western Netherlands, situated near the city of Leiden in the province of South Holland.
  • D. Roosendaal
    Roosendaal is a city in the southern Netherlands known as a regional center for commerce and transport near the Belgian border.
  • E. Barendrecht
    Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c3e5f9d08190861206934cd71fd8 completed March 1, 2026, 10:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65f9d763c81908bdc6d9cfc718a55 completed March 27, 2026, 10:44 a.m.
Created at: March 1, 2026, 7:59 p.m.