Triple

T8866810
Position Surface form Disambiguated ID Type / Status
Subject Margaret Whiting E211038 entity
Predicate name P16 FINISHED
Object Margaret Whiting E211038 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: Margaret Whiting | Statement: [Margaret Whiting, name, Margaret Whiting]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret Whiting
Context triple: [Margaret Whiting, name, Margaret Whiting]
  • A. Margaret Whiting chosen
    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.
  • B. Phyllis Calvert
    Phyllis Calvert was a prominent British film and stage actress, best known as one of the leading stars of 1940s British cinema.
  • C. Gloria DeHaven
    Gloria DeHaven was an American actress and singer best known for her roles in classic Hollywood musicals of the 1940s and 1950s.
  • D. 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.
  • E. Jo Stafford
    Jo Stafford was an American traditional pop and jazz singer renowned for her smooth vocal style and numerous hit recordings from the 1940s through the 1950s.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6108530c819084559f4de669ce20 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0dafdf48190abc1fe1a8397e339 completed April 3, 2026, 11:13 a.m.
Created at: March 30, 2026, 6:51 p.m.