Triple

T8395480
Position Surface form Disambiguated ID Type / Status
Subject Scott Silver E198041 entity
Predicate wrote P2831 FINISHED
Object Johns E732403 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: Johns | Statement: [Scott Silver, wrote, Johns]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johns
Context triple: [Scott Silver, wrote, Johns]
  • A. Johns
    Johns is a given name most notably associated with Johns Hopkins, the 19th-century American entrepreneur and philanthropist whose endowments founded Johns Hopkins University and Hospital.
  • B. Johns chosen
    "Johns" is a 1996 independent drama film centered on two hustlers in Los Angeles, known for its gritty portrayal of street life and early-career performances by actors like David Arquette.
  • C. Jones
    Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
  • D. The Johns
    The Johns is the informal nickname of the Regina Rifle Regiment, an infantry unit of the Canadian Army Reserve.
  • E. John
    John is the given name of the late Canadian actor and comedian John Candy, known for his roles in films like "Planes, Trains and Automobiles" and "Uncle Buck."
  • 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_69ca82f816bc8190ab321c07d72208c1 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb81874d6c8190bbc0ac832d8a339d completed March 31, 2026, 8:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce1d1ffa988190a7b0a6b1017e144d completed April 2, 2026, 7:39 a.m.
Created at: March 30, 2026, 6:04 p.m.