Triple

T8447667
Position Surface form Disambiguated ID Type / Status
Subject Cruel and Unusual Films E199715 entity
Predicate hasKeyPerson P256 FINISHED
Object Wesley Coller E733557 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: Wesley Coller | Statement: [Cruel and Unusual Films, hasKeyPerson, Wesley Coller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wesley Coller
Context triple: [Cruel and Unusual Films, hasKeyPerson, Wesley Coller]
  • A. Wesley Coller chosen
    Wesley Coller is an American film producer known for his longtime collaboration with director Zack Snyder on projects such as "300," "Watchmen," and "Man of Steel."
  • B. Blake Worsley
    Blake Worsley is a Canadian former competitive swimmer who specialized in freestyle events and represented Canada at international competitions, including the Olympic Games.
  • C. Wesley Cole
    Wesley Cole is a former CIA operative turned LAPD detective who serves as one of the main protagonists in the Lethal Weapon television series.
  • D. Wesley Jonathan
    Wesley Jonathan is an American actor best known for his roles in early-2000s television sitcoms and films, including the roller-skating comedy-drama "Roll Bounce."
  • E. Wesley Saunders
    Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
  • 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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe44480ec8190b32443a53cd4f943 completed March 31, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce39b528f08190a0627cb17a0ffef9 completed April 2, 2026, 9:41 a.m.
Created at: March 30, 2026, 6:09 p.m.