Triple

T8319011
Position Surface form Disambiguated ID Type / Status
Subject George Bannerman E194780 entity
Predicate partnerInInvestigation P24776 FINISHED
Object Johnny Smith E196432 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: Johnny Smith | Statement: [George Bannerman, partnerInInvestigation, Johnny Smith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johnny Smith
Context triple: [George Bannerman, partnerInInvestigation, Johnny Smith]
  • A. Johnny Smith chosen
    Johnny Smith is the psychic protagonist of Stephen King’s novel "The Dead Zone," whose visions of the future drive the story’s moral and political suspense.
  • B. Jimmy Smith
    Jimmy Smith was an influential American jazz organist whose innovative Hammond B-3 playing helped popularize soul jazz in the 1950s and 1960s.
  • C. Joe Smith
    Joe Smith is a former American professional basketball player and 1995 NBA first overall draft pick who starred as a forward at the University of Maryland.
  • D. Art Smith
    Art Smith is an American celebrity chef and restaurateur best known for his Southern-inspired cuisine and for serving as a personal chef to high-profile clients, including Oprah Winfrey.
  • E. Art Smith
    Art Smith was an American character actor known for his supporting roles in classic film noir and drama during the 1940s and 1950s.
  • 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_69ca82e7a8a88190a32bb5cc0feb012d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f648e10819081ad1fed870b2b86 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce6cc36a74819082713f53bb6755d7 completed April 2, 2026, 1:18 p.m.
Created at: March 30, 2026, 5:55 p.m.