Triple

T15126630
Position Surface form Disambiguated ID Type / Status
Subject Kathryn Hays E361306 entity
Predicate spouse P13 FINISHED
Object Glenn Ford E250405 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: Glenn Ford | Statement: [Kathryn Hays, spouse, Glenn Ford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glenn Ford
Context triple: [Kathryn Hays, spouse, Glenn Ford]
  • A. Glenn Ford chosen
    Glenn Ford was a Canadian-American film actor renowned for his versatile performances in classic Hollywood movies such as "Gilda," "The Big Heat," and "Blackboard Jungle."
  • B. Richard Widmark
    Richard Widmark was an American film and television actor renowned for his intense portrayals in film noir and Westerns, particularly during Hollywood’s mid-20th-century era.
  • C. Ray Taylor
    Ray Taylor was an American film director best known for his work on action-packed serials and B-movies during the early 20th century.
  • D. Alan Ladd
    Alan Ladd was an American film actor best known for his cool, understated performances in classic movies such as the Western "Shane."
  • E. Dana Andrews
    Dana Andrews was a prominent American film actor of the 1940s and 1950s, best known for his leading roles in classics such as "Laura" and "The Best Years of Our Lives."
  • 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_69d85a06450081909c5a14ea9851a15e completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005a1b9288190954f2d92549805e5 completed April 15, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a004f3548b48190aec852723654bd35 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 3:06 a.m.