Triple

T17645302
Position Surface form Disambiguated ID Type / Status
Subject Rivierenland E429339 entity
Predicate contains P35 FINISHED
Object Buren NE NERFINISHED

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: Buren | Statement: [Rivierenland, contains, Buren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buren
Context triple: [Rivierenland, contains, Buren]
  • A. Buren chosen
    Buren is a historic Dutch town in the province of Gelderland, known for its ties to the Dutch royal family and its well-preserved medieval character.
  • B. Buren
    Buren is the entomologist who formally described the invasive red imported fire ant species Solenopsis invicta.
  • C. Bracq
    Bracq is a French surname most notably associated with Paul Bracq, a renowned automotive designer known for his influential work with Mercedes-Benz and BMW.
  • D. Peynet
    Peynet is the surname of French illustrator Raymond Peynet, best known for his romantic "lovers" drawings that became iconic in mid-20th-century France.
  • E. Baulmes
    Baulmes is a Swiss village and municipality in the canton of Vaud, situated near the Jura Mountains and known for its scenic rural landscape.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46e382ba88190af19d0e3b8c8cadd completed April 19, 2026, 5:55 a.m.
Created at: April 10, 2026, 6:04 a.m.