Triple

T3110159
Position Surface form Disambiguated ID Type / Status
Subject HMS Victory E64930 entity
Predicate notableCommander P1197 FINISHED
Object John Jervis E298820 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 Jervis | Statement: [HMS Victory, notableCommander, John Jervis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Jervis
Context triple: [HMS Victory, notableCommander, John Jervis]
  • A. John Jervis chosen
    John Jervis was a prominent 18th-century British admiral who became Earl of St Vincent and was renowned for his decisive naval victories during the French Revolutionary Wars.
  • B. Geoffrey Jellicoe
    Geoffrey Jellicoe was a prominent British landscape architect and garden designer known for his influential 20th-century public and private landscape projects.
  • C. John Blatchley
    John Blatchley was a British theatre director and educator best known as a co-founder of the influential Drama Centre London acting school.
  • D. Sir John Woodcock
    Sir John Woodcock was a prominent British police officer who served as Chief Constable of several forces and later as Her Majesty’s Chief Inspector of Constabulary.
  • E. Pembroke J. Herring
    Pembroke J. Herring was an American film editor known for his work on numerous major Hollywood comedies and dramas from the 1960s through the 1990s.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada437c5e08190af22f6fa11cf9252 completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b203902a6881909b20589fad629640 completed March 12, 2026, 12:06 a.m.
Created at: March 8, 2026, 3:04 p.m.