Triple

T5636028
Position Surface form Disambiguated ID Type / Status
Subject Angela Bassett E147950 entity
Predicate surname P18 FINISHED
Object Bassett E147950 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: Bassett | Statement: [Angela Bassett, surname, Bassett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bassett
Context triple: [Angela Bassett, surname, Bassett]
  • A. Bassett chosen
    Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
  • B. Cavalier
    Cavalier is the costumed mascot character representing the University of Virginia’s athletic teams, typically depicted as a historical Virginia cavalryman.
  • C. Cavalier
    Cavalier is the first name of Cavalier Johnson, an American politician serving as the mayor of Milwaukee, Wisconsin.
  • D. Barkly
    Barkly is a vast electoral division in Australia's Northern Territory, encompassing remote outback communities and pastoral regions including the Tennant Creek area.
  • E. Tolhuin
    Tolhuin is a small town in the Argentine part of Tierra del Fuego, known for its location on the shores of Lake Fagnano between Ushuaia and Río Grande.
  • 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_69c00907bc8881909ed760d3ed73ef35 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0226286208190b6ccf036cc09fe82 completed March 22, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a1666d88190af4c1890247f897d completed March 22, 2026, 9:07 p.m.
Created at: March 22, 2026, 3:41 p.m.