Triple

T4627302
Position Surface form Disambiguated ID Type / Status
Subject Clarence Brown E101128 entity
Predicate workedWith P398 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: [Clarence Brown, workedWith, Clark Gable]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clark Gable
Context triple: [Clarence Brown, workedWith, 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a2e9780819081add547c760abc9 completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c7add98819089fbff1a21a19e28 completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:13 p.m.