Triple

T18305801
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Griscom E438479 entity
Predicate spouse P13 FINISHED
Object John Ross — NE NERFINISHED

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 Ross | Statement: [Elizabeth Griscom, spouse, John Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Ross
Context triple: [Elizabeth Griscom, spouse, John Ross]
  • A. John Ross chosen
    John Ross was the first husband of Betsy Ross, traditionally credited with helping her establish an upholstery business in Philadelphia before his early death during the American Revolutionary era.
  • B. John Ross
    John Ross was a 19th-century Scottish naval officer and Arctic explorer noted for his early expeditions in search of the Northwest Passage.
  • C. John Ross
    John Ross was a prominent 19th-century Cherokee chief who led his people through the era of forced removal known as the Trail of Tears.
  • D. Frank Ross
    Frank Ross was an American film producer known for his work on major mid-20th-century Hollywood productions.
  • E. Frank Ross
    Frank Ross is a fictional rancher whose murder sets the revenge-driven plot in Charles Portis's novel "True Grit" into motion.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50183394081909b86cefaaa0a3aa8 completed April 19, 2026, 4:23 p.m.
Created at: April 10, 2026, 10:35 a.m.