Triple

T8068342
Position Surface form Disambiguated ID Type / Status
Subject Edith Louisa Sylvia Hawkes E188300 entity
Predicate spouse P13 FINISHED
Object Clark Gable E15035 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: Clark Gable | Statement: [Edith Louisa Sylvia Hawkes, spouse, Clark Gable]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clark Gable
Context triple: [Edith Louisa Sylvia Hawkes, spouse, Clark Gable]
  • A. Clark Gable chosen
    Clark Gable was a legendary American film actor, best known for his charismatic leading roles in classic Hollywood films such as "Gone with the Wind."
  • B. John Clark Gable
    John Clark Gable is an American former racing driver and the only son of legendary Hollywood actor Clark Gable.
  • C. Gary Cooper
    Gary Cooper was an iconic American film actor renowned for his understated, stoic performances in classic Hollywood films, including major roles in Westerns and dramas.
  • D. Humphrey Bogart
    Humphrey Bogart was an iconic American film actor best known for his tough yet vulnerable screen persona in classic films such as "Casablanca" and "The Maltese Falcon."
  • E. Melvyn Douglas
    Melvyn Douglas was an acclaimed American actor known for his sophisticated screen presence and award-winning performances in both classic Hollywood films and later character roles.
  • 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_69ca82b42674819086840efea12478e5 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ff8a4fc8190a97fc7111ca7ec4d completed March 31, 2026, 3:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd341a2d2081909e812361025dc1cb completed April 1, 2026, 3:04 p.m.
Created at: March 30, 2026, 5:27 p.m.