Triple

T7560873
Position Surface form Disambiguated ID Type / Status
Subject Unforgiven E178790 entity
Predicate starring P1507 FINISHED
Object Gene Hackman E248765 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: Gene Hackman | Statement: [Unforgiven, starring, Gene Hackman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gene Hackman
Context triple: [Unforgiven, starring, Gene Hackman]
  • A. Gene Hackman chosen
    Gene Hackman is an acclaimed American actor known for his powerful, versatile performances in films such as "The French Connection," "The Conversation," and "Unforgiven."
  • B. Jon Voight
    Jon Voight is an American actor acclaimed for his powerful performances in films such as "Midnight Cowboy," "Deliverance," and "Coming Home," for which he won the Academy Award for Best Actor.
  • C. Ned Beatty
    Ned Beatty was an acclaimed American character actor known for his powerful supporting roles in films such as "Deliverance," "Network," and "Superman."
  • D. Nick Nolte
    Nick Nolte is an American actor known for his rugged screen presence and acclaimed performances in films such as "The Prince of Tides," "Affliction," and "48 Hrs."
  • E. Jeff Bridges
    Jeff Bridges is an acclaimed American actor known for his versatile performances in films such as "The Big Lebowski," "Crazy Heart," and "True Grit."
  • 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_69c69f2f80288190b95cceb4da92ab2b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8f847c48190a1081aa9de7ff945 completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856d0cbfc8190b2cb2b601a7b078c completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:50 p.m.