Triple

T8516297
Position Surface form Disambiguated ID Type / Status
Subject Tony Scott E201579 entity
Predicate workedWith P398 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: [Tony Scott, workedWith, Gene Hackman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gene Hackman
Context triple: [Tony Scott, workedWith, 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe62550908190af882019d68a904a completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce88ec84208190ab72c8411e6cc4c2 completed April 2, 2026, 3:19 p.m.
Created at: March 30, 2026, 6:15 p.m.