Triple

T17577915
Position Surface form Disambiguated ID Type / Status
Subject Wynberg E428119 entity
Predicate locatedNear P294 FINISHED
Object Kenilworth 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: Kenilworth | Statement: [Wynberg, locatedNear, Kenilworth]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenilworth
Context triple: [Wynberg, locatedNear, Kenilworth]
  • A. Kenilworth
    Kenilworth is a historic market town in central England best known for the extensive ruins of Kenilworth Castle and its connections to Tudor and medieval history.
  • B. Kenilworth chosen
    Kenilworth is a residential suburb in Cape Town, South Africa, known for its tree-lined streets, mixed-use character, and proximity to major schools and transport routes.
  • C. Kenilworth
    Kenilworth is a small rural town in Queensland’s Sunshine Coast hinterland known for its scenic countryside, dairy farming, and outdoor recreation.
  • D. Warwick
    Warwick is a surname of English origin borne by various notable individuals and families, including members of the Drinkard and Warwick musical families.
  • E. Warwick
    Warwick is a central character in the 1990 horror film "Graveyard Shift," known for his role in the sinister events that unfold in the movie's haunted textile mill.
  • 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e463cb40088190b726f2c026358cf2 completed April 19, 2026, 5:10 a.m.
Created at: April 10, 2026, 5:50 a.m.