Triple

T8157268
Position Surface form Disambiguated ID Type / Status
Subject Brenda de Banzie E190480 entity
Predicate placeOfDeath P21 FINISHED
Object Brighton E45112 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: Brighton | Statement: [Brenda de Banzie, placeOfDeath, Brighton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brighton
Context triple: [Brenda de Banzie, placeOfDeath, Brighton]
  • A. Brighton
    Brighton is a small city in Colorado that forms part of the Denver metropolitan area along the Front Range of the Rocky Mountains.
  • B. Brighton
    Brighton is a residential neighborhood in the western part of Boston, Massachusetts, known for its mix of students, young professionals, and long-time residents.
  • C. Brighton
    Brighton is a small mountain resort town in Utah known for its ski area, alpine scenery, and outdoor recreation.
  • D. Brighton
    Brighton is a small municipality in southeastern Ontario, Canada, known for its rural charm, proximity to Lake Ontario, and nearby Presqu’ile Provincial Park.
  • E. Brighton chosen
    Brighton is a major seaside city on England’s south coast, renowned for its beach, pier, and vibrant cultural and nightlife scenes.
  • 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb44da14a481909f8d3277762b0e75 completed March 31, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbe17811081909c19f18c853617af completed April 1, 2026, 6:41 a.m.
Created at: March 30, 2026, 5:37 p.m.