Triple

T2232307
Position Surface form Disambiguated ID Type / Status
Subject See No Evil, Hear No Evil E49196 entity
Predicate storyBy P1955 FINISHED
Object Earl Barret E264095 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: Earl Barret | Statement: [See No Evil, Hear No Evil, storyBy, Earl Barret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Earl Barret
Context triple: [See No Evil, Hear No Evil, storyBy, Earl Barret]
  • A. Earl Barret chosen
    Earl Barret is a screenwriter best known for his work on the 1989 comedy film "See No Evil, Hear No Evil."
  • B. Cliff Hagan
    Cliff Hagan is an American Hall of Fame basketball player best known for his scoring prowess with the St. Louis Hawks and later as a player-coach in the ABA.
  • C. Eddie Spears
    Eddie Spears is a Native American actor known for his roles in film and television, particularly in Western and Indigenous-themed productions.
  • D. Earl Hurd
    Earl Hurd was an American animator, director, and writer best known as a pioneer of cel animation and an influential early figure in the development of animated films.
  • E. Earle Kingston
    Earle Kingston is the husband of acclaimed Chinese American author Maxine Hong Kingston.
  • 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_69a88aa84bdc819086df50e9c20b301e completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc06d26bc8190a85ddb6312d2df08 completed March 7, 2026, 6:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f76bb60819084cac16bce2ce55d completed March 9, 2026, 7:28 p.m.
Created at: March 4, 2026, 7:47 p.m.