Triple

T19351524
Position Surface form Disambiguated ID Type / Status
Subject Carter De Haven E484030 entity
Predicate child P120 FINISHED
Object Gloria DeHaven E131598 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: Gloria DeHaven | Statement: [Carter De Haven, child, Gloria DeHaven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gloria DeHaven
Context triple: [Carter De Haven, child, Gloria DeHaven]
  • A. Gloria DeHaven chosen
    Gloria DeHaven was an American actress and singer best known for her roles in classic Hollywood musicals of the 1940s and 1950s.
  • B. Helen Merrill
    Helen Merrill is an American jazz vocalist renowned for her cool, introspective style and influential recordings with leading jazz musicians of the 1950s.
  • C. Margaret Whiting
    Margaret Whiting was an American traditional pop and country music singer prominent in the 1940s and 1950s, known for her smooth vocal style and numerous hit recordings.
  • D. Ava Starr
    Ava Starr is the Marvel Cinematic Universe character known as Ghost, a quantumly unstable antagonist-turned-antihero who appears in "Ant-Man and the Wasp."
  • E. Gladys Lehman
    Gladys Lehman was an American screenwriter active during Hollywood’s classic era, known for her work on several notable studio films.
  • 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_69d8e8d244f8819080eb1f3491300db2 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e61904a878819084d58ed3b7d8a978 completed April 20, 2026, 12:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a072b75a2108190bce47e8156734593 completed May 15, 2026, 2:19 p.m.
Created at: April 10, 2026, 1:34 p.m.