Triple

T10844704
Position Surface form Disambiguated ID Type / Status
Subject Sharpe E255980 entity
Predicate mainCharacter P1183 FINISHED
Object Richard Sharpe E255981 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: Richard Sharpe | Statement: [Sharpe, mainCharacter, Richard Sharpe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Sharpe
Context triple: [Sharpe, mainCharacter, Richard Sharpe]
  • A. Richard Sharpe chosen
    Richard Sharpe is the fictional British soldier and officer from Bernard Cornwell’s historical novels, best known through the television adaptations in which he rises through the ranks during the Napoleonic Wars.
  • B. Richard Bowdler Sharpe
    Richard Bowdler Sharpe was a 19th-century English zoologist and ornithologist known for his extensive work on bird classification and descriptions, including numerous species of raptors.
  • C. Outram
    Outram is a central district in Singapore known for its major medical facilities, heritage architecture, and proximity to the downtown core.
  • D. Outram
    Outram is an English surname historically associated with several notable figures, including British military officers and public servants.
  • E. Sharpe
    Sharpe is the surname of Shannon Sharpe, a Hall of Fame former NFL tight end and prominent sports analyst.
  • 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_69d6aa81a5d08190aa86689061d1ddd2 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d750d0155c81908fb55ba6b45db800 completed April 9, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb153de988190bd48f1c1980d7ca2 completed April 14, 2026, 9:27 p.m.
Created at: April 8, 2026, 9:19 p.m.