Triple

T12588310
Position Surface form Disambiguated ID Type / Status
Subject Edward Platt E300527 entity
Predicate name P16 FINISHED
Object Edward Platt E300527 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: Edward Platt | Statement: [Edward Platt, name, Edward Platt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edward Platt
Context triple: [Edward Platt, name, Edward Platt]
  • A. Edward Platt chosen
    Edward Platt was an American character actor best known for playing the Chief in the television series "Get Smart" and for roles in several classic mid-20th-century films.
  • B. Edward Talbot
    Edward Talbot was an Anglican clergyman who became the inaugural Bishop of Southwark in the Church of England.
  • C. Edward Blount
    Edward Blount was a prominent early 17th-century London stationer and publisher best known for co-publishing Shakespeare’s First Folio.
  • D. Richard Talbot
    Richard Talbot was a 17th-century Irish soldier and statesman who became a leading Jacobite figure and Lord Deputy of Ireland under King James II.
  • E. William Pleeth
    William Pleeth was a renowned British cellist and influential teacher best known for mentoring the celebrated cellist Jacqueline du Pré.
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954bd5e8c8190a2f233b91682341f completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671926a7c8190a41725cfde7836b1 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:06 p.m.