Triple

T10014489
Position Surface form Disambiguated ID Type / Status
Subject The White Shadow E199451 entity
Predicate notableCastMember P7010 FINISHED
Object Ken Howard E536638 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: Ken Howard | Statement: [The White Shadow, notableCastMember, Ken Howard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ken Howard
Context triple: [The White Shadow, notableCastMember, Ken Howard]
  • A. Ken Howard chosen
    Ken Howard was an American actor best known for his roles in film, television, and theater, including his portrayal of Thomas Jefferson in the musical film "1776."
  • B. Donald Howard
    Donald Howard was a British politician best known for serving on the controversial Simon Commission that investigated constitutional reform in colonial India.
  • C. Steve Howard
    Steve Howard is a British trumpeter best known for his work with Paul McCartney and Wings during the 1970s.
  • D. Peter Howard
    Peter Howard was a prominent American musical theatre orchestrator and dance music arranger known for his work on numerous Broadway productions.
  • E. J. Scott Howard
    J. Scott Howard is a composer and musician best known for creating the musical score for the independent horror-comedy film "Baghead."
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd49b19c8190b429e3533d072648 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d94ae0a9608190ab241b6a62fe807b completed April 10, 2026, 7:09 p.m.
Created at: March 30, 2026, 8:52 p.m.