Triple

T15209739
Position Surface form Disambiguated ID Type / Status
Subject John Fairfield E363483 entity
Predicate name P16 FINISHED
Object John Fairfield E363483 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: John Fairfield | Statement: [John Fairfield, name, John Fairfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Fairfield
Context triple: [John Fairfield, name, John Fairfield]
  • A. John Fairfield chosen
    John Fairfield was a 19th-century American politician and governor of Maine who played a key leadership role during the Aroostook War, a border dispute between the United States and British North America.
  • B. David Abercrombie
    David Abercrombie was a British phonetician and linguist known for his influential work on phonetics and the study of spoken English.
  • C. John Bloomfield
    John Bloomfield is a British costume designer best known for his work on major fantasy and adventure films, including "Conan the Destroyer."
  • D. John Fields
    John Fields is an American record producer and musician known for his work with pop and rock artists such as the Jonas Brothers, Demi Lovato, and Switchfoot.
  • E. John Truett
    John Truett is the charming boy-next-door love interest of Esther Smith in the classic 1944 musical film "Meet Me in St. Louis."
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076ad4ec81908d36f541fca08d72 completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed33f9abc8190bf8166c1fd9fcac6 completed May 9, 2026, 6:25 a.m.
Created at: April 10, 2026, 3:11 a.m.