Triple

T18927867
Position Surface form Disambiguated ID Type / Status
Subject John Ross E463020 entity
Predicate name P16 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: [John Ross, name, John Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Ross
Context triple: [John Ross, name, John Ross]
  • A. John Ross
    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 is a central character in Terry Brooks' urban fantasy "Word & Void" series, a former lawyer turned Knight of the Word who battles demonic forces to protect the future of humanity.
  • D. 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.
  • E. Frank Ross
    Frank Ross was an American film producer known for his work on major mid-20th-century Hollywood productions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c9bdddb481908bebd32f927ed5de completed April 20, 2026, 6:37 a.m.
Created at: April 10, 2026, 11:59 a.m.