Triple

T19973271
Position Surface form Disambiguated ID Type / Status
Subject Henry Ward Ranger E480131 entity
Predicate name P16 FINISHED
Object Henry Ward Ranger — 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: Henry Ward Ranger | Statement: [Henry Ward Ranger, name, Henry Ward Ranger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Henry Ward Ranger
Context triple: [Henry Ward Ranger, name, Henry Ward Ranger]
  • A. Henry Ward Ranger chosen
    Henry Ward Ranger was an American painter known for his atmospheric landscapes and as a leading figure in the Tonalist movement at the turn of the 20th century.
  • B. Ralph Dixon
    Ralph Dixon was a film editor active during the silent era of American cinema.
  • C. Lewis Branscomb
    Lewis Branscomb was an American physicist and influential science and technology policy leader known for his work at the intersection of research, innovation, and public policy.
  • D. Asa Biggs
    Asa Biggs was a 19th-century American politician from North Carolina who served as a U.S. Representative, U.S. Senator, and later a federal judge.
  • E. Hugh Wiley
    Hugh Wiley was an American writer best known for creating the fictional Chinese-American detective James Lee Wong, who appeared in a series of stories and film adaptations.
  • 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_69d8e523c19881909f9197037200dde6 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65bcb72048190aedb4f085ace0493 completed April 20, 2026, 5 p.m.
Created at: April 10, 2026, 1:54 p.m.