Triple

T11981544
Position Surface form Disambiguated ID Type / Status
Subject Anne Page E285171 entity
Predicate father P120 FINISHED
Object George Page E958129 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: George Page | Statement: [Anne Page, father, George Page]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Page
Context triple: [Anne Page, father, George Page]
  • A. George Page chosen
    George Page is a character in William Shakespeare’s comedy "The Merry Wives of Windsor," known as the respectable husband of Mistress Page.
  • B. Leo Dryden
    Leo Dryden was a popular late 19th- and early 20th-century British music hall singer known as the "Kipling of the Halls" for his patriotic and sentimental ballads.
  • C. Harold Briggs
    Harold Briggs was a British Army officer best known for devising and implementing the Briggs Plan to combat communist insurgency during the Malayan Emergency.
  • D. George Stanley
    George Stanley was an American sculptor best known for designing the iconic Oscar statuette for the Academy Awards.
  • E. George Stanley
    George Stanley was a Canadian-born poet and educator associated with the San Francisco Renaissance literary movement.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90395a8788190bfbb3506c29e3825 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f49d0791348190a2f6c0e808af3aea completed May 1, 2026, 12:31 p.m.
Created at: April 8, 2026, 9:46 p.m.