Triple

T8059020
Position Surface form Disambiguated ID Type / Status
Subject Roy Rodgers E188069 entity
Predicate hasNameComponent P24447 FINISHED
Object Rodgers E36063 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: Rodgers | Statement: [Roy Rodgers, hasNameComponent, Rodgers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rodgers
Context triple: [Roy Rodgers, hasNameComponent, Rodgers]
  • A. Rodgers chosen
    Rodgers is a surname of Scottish and Irish origin borne by various notable individuals across sports, entertainment, and other fields.
  • B. Mat Rogers
    Mat Rogers is an Australian former dual-code rugby international who played both rugby league and rugby union at elite levels, including representing Australia and starring in the NRL.
  • C. Ab Rogers
    Ab Rogers is a British designer and architect known for his innovative, playful interior and exhibition designs and for founding Ab Rogers Design.
  • D. Rodger Dodger
    Rodger Dodger is a 2002 dark comedy-drama film about a cynical New York advertising executive who spends a night trying to teach his teenage nephew how to seduce women.
  • E. Rogers Morton
    Rogers Morton was an American Republican politician who served as U.S. Secretary of the Interior and later Secretary of Commerce in the 1970s.
  • 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_69ca82b2f68881908c50560697e210da completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3fa51adc8190b9327441bd8b9fb3 completed March 31, 2026, 3:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc63d6484c8190b2fd2c2bef179fc4 completed April 1, 2026, 12:16 a.m.
Created at: March 30, 2026, 5:25 p.m.