Triple

T3519812
Position Surface form Disambiguated ID Type / Status
Subject John Teller E74393 entity
Predicate givenName P17 FINISHED
Object John E55602 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 | Statement: [John Teller, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Teller, givenName, John]
  • A. John chosen
    John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
  • B. John
    John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
  • C. John
    John is the given name of John Reith, the influential first Director-General of the BBC who shaped early public service broadcasting in the United Kingdom.
  • D. John
    John is the given name of John F. Sattler, likely referring to him in a more informal or abbreviated context.
  • E. John
    John "Stuffy" McInnis was an American Major League Baseball first baseman best known as a member of Connie Mack’s Philadelphia Athletics dynasty in the early 20th century.
  • 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_69ad85d0c5488190a3d8e02ebd01a1aa completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc4af70c8190a7471f28e1efd7fd completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e848d1c8190b100cb2e1218afbb completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.