Triple

T6540366
Position Surface form Disambiguated ID Type / Status
Subject Brad Renfro E168269 entity
Predicate coStarredWith P14987 FINISHED
Object Mickey Rourke E237839 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: Mickey Rourke | Statement: [Brad Renfro, coStarredWith, Mickey Rourke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mickey Rourke
Context triple: [Brad Renfro, coStarredWith, Mickey Rourke]
  • A. Mickey Rourke chosen
    Mickey Rourke is an American actor and former boxer known for his intense, brooding performances in films such as "The Wrestler," "9½ Weeks," and "Angel Heart."
  • B. Tim Roth
    Tim Roth is an English actor known for his intense, often villainous roles in films such as "Reservoir Dogs," "Pulp Fiction," and "Rob Roy," as well as his collaborations with directors like Quentin Tarantino.
  • C. Val Kilmer
    Val Kilmer is an American actor known for his versatile performances in films such as "Top Gun," "The Doors," and "Batman Forever."
  • D. Michael Clarke Duncan
    Michael Clarke Duncan was an American actor best known for his Oscar-nominated performance as the gentle giant John Coffey in the film "The Green Mile."
  • E. Nicolas Cage
    Nicolas Cage is an American actor known for his intense and eclectic performances across action, drama, and independent films.
  • 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_69c68a51564081909e93aee0dbd9cca3 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6add7369c8190919cd7c07012a994 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d53edf108190b74098b41c143a65 completed March 27, 2026, 7:06 p.m.
Created at: March 27, 2026, 1:50 p.m.