Triple

T19627811
Position Surface form Disambiguated ID Type / Status
Subject 3000 Miles to Graceland E471183 entity
Predicate starring P1507 FINISHED
Object Kurt Russell NE NERFINISHED

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: Kurt Russell | Statement: [3000 Miles to Graceland, starring, Kurt Russell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kurt Russell
Context triple: [3000 Miles to Graceland, starring, Kurt Russell]
  • A. Kurt Russell chosen
    Kurt Russell is an American actor known for his versatile performances in films ranging from action and science fiction to drama and comedy, including iconic roles in movies like "Escape from New York," "The Thing," and "Tombstone."
  • B. Sam Haskell
    Sam Haskell is an American television producer and former talent agent known for developing and producing family-oriented TV specials and films.
  • C. Fred Ward
    Fred Ward was an American character actor known for his rugged, everyman roles in films such as "Tremors," "The Right Stuff," and "Short Cuts."
  • D. James A. Woods
    James A. Woods is a Canadian actor and screenwriter best known for co-writing the science fiction film "Independence Day: Resurgence."
  • E. Tom Berenger
    Tom Berenger is an American actor best known for his roles in films such as "Platoon," "The Big Chill," and "Inception," often portraying tough, complex characters.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e641007e5881908da78e50aa36f340 completed April 20, 2026, 3:06 p.m.
Created at: April 10, 2026, 1:44 p.m.