Triple

T14228485
Position Surface form Disambiguated ID Type / Status
Subject Inspector Gadget E352688 entity
Predicate fullName P16 FINISHED
Object Jonathan John Brown E971834 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: Jonathan John Brown | Statement: [Inspector Gadget, fullName, Jonathan John Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonathan John Brown
Context triple: [Inspector Gadget, fullName, Jonathan John Brown]
  • A. Jonathan Brown chosen
    Jonathan Brown is an individual known primarily as the son of Mr. Brown.
  • B. Jonathan Brown
    Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
  • C. Michael Henry Brown
    Michael Henry Brown is a screenwriter best known for his work on the crime thriller film "In Too Deep."
  • D. Ian Browne
    Ian Browne is a Canadian musician best known as the drummer for the rock band Matthew Good Band.
  • E. Anthony Gregory Brown
    Anthony Gregory Brown is an American politician and attorney who has served as Maryland's Attorney General and previously as the state's lieutenant governor and a U.S. Representative.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de622a48508190bbfedb762bd1674d completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3251ec5881909fcebc9477d6a761 completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:07 a.m.