Triple

T12452304
Position Surface form Disambiguated ID Type / Status
Subject Ben & Jerry's E297559 entity
Predicate hasKeyPerson P256 FINISHED
Object Jerry Greenfield E985222 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: Jerry Greenfield | Statement: [Ben & Jerry's, hasKeyPerson, Jerry Greenfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerry Greenfield
Context triple: [Ben & Jerry's, hasKeyPerson, Jerry Greenfield]
  • A. Jerry Greenfield chosen
    Jerry Greenfield is an American businessman and philanthropist best known as the co-founder of the ice cream company Ben & Jerry's.
  • B. John Greenfield
    John Greenfield was an individual significant enough in local or regional history that the city of Greenfield, California, was named in his honor.
  • C. Sam Greenfield
    Sam Greenfield is the perpetually unlucky young woman who becomes the central heroine of the animated fantasy film "Luck," navigating a secret world of good and bad fortune.
  • D. Daniel Green
    Daniel Green is a music producer known for his work on the track "Paradise."
  • E. Martin Green
    Martin Green is a renowned Australian engineer and solar energy researcher recognized as a leading pioneer in photovoltaic technology.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94da0b5988190b9df26dd3bb87337 completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b9f4dd08190b1d62b03d68cc8a6 completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:56 p.m.