Triple

T15623876
Position Surface form Disambiguated ID Type / Status
Subject William Stryker E375630 entity
Predicate portrayedBy P1507 FINISHED
Object Brian Cox E70759 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: Brian Cox | Statement: [William Stryker, portrayedBy, Brian Cox]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brian Cox
Context triple: [William Stryker, portrayedBy, Brian Cox]
  • A. Brian Cox chosen
    Brian Cox is a Scottish actor known for his powerful performances in film, television, and theater, including roles in movies like "The Long Kiss Goodnight" and the TV series "Succession."
  • B. Brian Cox
    Brian Cox is a British physicist and popular science communicator known for presenting BBC science programs and making complex physics accessible to the public.
  • C. Brian Michael Cox
    Brian Michael Cox is a Grammy-winning American songwriter and record producer known for his work on numerous R&B and pop hits.
  • D. George Norton
    George Norton was a British colonial-era lawyer and educator best known for establishing Presidency College in Madras, one of India’s earliest and most prestigious institutions of higher learning.
  • E. Bruce Greenwood
    Bruce Greenwood is a Canadian actor known for his versatile roles in film and television, including prominent performances in projects like "Star Trek," "Thirteen Days," and numerous acclaimed dramas.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9cfd94819091459aa17a002eaf completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f3f65dc8190ac94db1d4d53d77f completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:14 a.m.