Triple

T15177552
Position Surface form Disambiguated ID Type / Status
Subject Beaver Club E362649 entity
Predicate hasMember P10 FINISHED
Object John Ross E463020 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 Ross | Statement: [Beaver Club, hasMember, John Ross]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Ross
Context triple: [Beaver Club, hasMember, 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 chosen
    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 (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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00663b4148190b647592eda315d1d completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec89061548190b0b10da00b8d937e completed May 9, 2026, 5:39 a.m.
Created at: April 10, 2026, 3:09 a.m.