Triple

T4860582
Position Surface form Disambiguated ID Type / Status
Subject King's Men E108647 entity
Predicate notableMember P10 FINISHED
Object John Heminges E410808 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 Heminges | Statement: [King's Men, notableMember, John Heminges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Heminges
Context triple: [King's Men, notableMember, John Heminges]
  • A. John Heminges chosen
    John Heminges was an English actor and theatrical manager best known for helping compile and publish Shakespeare’s First Folio in 1623.
  • B. Hamnet Shakespeare
    Hamnet Shakespeare was the only son of playwright William Shakespeare, whose early death at age 11 is often thought to have influenced his father's later works.
  • C. John Shakespeare
    John Shakespeare was an English glover, wool dealer, and municipal official in Stratford-upon-Avon, best known as the father of playwright William Shakespeare.
  • D. William Heath
    William Heath was a Continental Army general during the American Revolutionary War who later became a prominent Massachusetts politician and judge.
  • E. Edward Alleyn
    Edward Alleyn was a prominent Elizabethan actor and theatre entrepreneur who became a wealthy philanthropist and educational benefactor in London.
  • 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_69bd440b965081908b0557721cae6338 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d5e247c8190b6ae4e9b529f0345 completed March 20, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cf49590819084de6b655f1c8e88 completed March 21, 2026, 8:55 a.m.
Created at: March 20, 2026, 1:26 p.m.