Triple

T4945560
Position Surface form Disambiguated ID Type / Status
Subject Baarn E111040 entity
Predicate hasPart P35 FINISHED
Object Baarn (town) E111040 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: Baarn (town) | Statement: [Baarn, hasPart, Baarn (town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baarn (town)
Context triple: [Baarn, hasPart, Baarn (town)]
  • A. Baarn chosen
    Baarn is a town and municipality in the Dutch province of Utrecht, known for its historic royal connections and green, affluent residential character.
  • B. Hodenhagen
    Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
  • C. Staaken
    Staaken is a locality in western Berlin, Germany, known for its residential areas and historical role as part of the Spandau district near the former inner-German border.
  • D. Bockum
    Bockum is a residential district of the German city of Krefeld, known for its green spaces and affluent neighborhoods.
  • E. Ballstad
    Ballstad is a fishing village in Norway’s Lofoten archipelago, known for its scenic coastal landscape and traditional maritime culture.
  • 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_69bd441721cc819085c7e33fe0876818 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd70aa890c81908e685ec5e88cae1f completed March 20, 2026, 4:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77c6566c8190b0c76c05b9d82053 completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:31 p.m.