Triple

T4083532
Position Surface form Disambiguated ID Type / Status
Subject Reinier de Graaf E87534 entity
Predicate birthPlace P1 FINISHED
Object Schoonhoven E527517 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: Schoonhoven | Statement: [Reinier de Graaf, birthPlace, Schoonhoven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schoonhoven
Context triple: [Reinier de Graaf, birthPlace, Schoonhoven]
  • A. Schoonhoven chosen
    Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
  • B. Veldhoven
    Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
  • C. Woerden
    Woerden is a historic Dutch city and municipality in the central Netherlands, known for its medieval fortifications and traditional cheese market.
  • 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_69aed9435cf48190ad1da737c962d19d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc7933b481909bb3e02c6c04c8ee completed March 9, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d20c75bf508190a812c87950cb5227 completed April 5, 2026, 7:17 a.m.
Created at: March 9, 2026, 3:39 p.m.