Triple

T7049619
Position Surface form Disambiguated ID Type / Status
Subject Green Mansions E163730 entity
Predicate stars P1956 FINISHED
Object Henry Silva E518284 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: Henry Silva | Statement: [Green Mansions, stars, Henry Silva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Henry Silva
Context triple: [Green Mansions, stars, Henry Silva]
  • A. Henry Silva chosen
    Henry Silva was an American character actor known for his intense, often villainous roles in films such as "The Manchurian Candidate" and numerous crime and action movies from the 1950s through the 1990s.
  • B. Mel Ferrer
    Mel Ferrer was an American actor, director, and producer known for his work in classic Hollywood films and his marriage to Audrey Hepburn.
  • C. Ernest Borgnine
    Ernest Borgnine was an American actor known for his gruff but endearing screen presence and an Academy Award–winning performance in the film "Marty."
  • D. Enrique Castro
    Enrique Castro is a member of the Castro family of Cuba, known primarily as a sibling of revolutionary figures Fidel, Raúl, and Juanita Castro.
  • E. Lionel Stander
    Lionel Stander was an American character actor known for his distinctive gravelly voice and memorable supporting roles in classic Hollywood films and later television.
  • 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_69c6885f598c8190b6b6495c59d8d962 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e24d5e8c8190b37e56107e6da8ab completed March 27, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79c857ca08190a964861cb7aff86a completed March 28, 2026, 9:16 a.m.
Created at: March 27, 2026, 2:37 p.m.