Triple

T17890715
Position Surface form Disambiguated ID Type / Status
Subject David Brown E447307 entity
Predicate employer P7 FINISHED
Object Aston Martin NE NERFINISHED

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: Aston Martin | Statement: [David Brown, employer, Aston Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aston Martin
Context triple: [David Brown, employer, Aston Martin]
  • A. Aston Martin chosen
    Aston Martin is a British luxury sports car manufacturer renowned for its high-performance grand tourers and long association with the James Bond film franchise.
  • B. Bentley
    Bentley is a British luxury automobile manufacturer renowned for its high-performance grand tourers and handcrafted interiors.
  • C. Bentley
    Bentley is a small rural village and civil parish in East Hampshire, England, known for its countryside setting and traditional English character.
  • D. Bentley
    Bentley is a surname of English origin borne by various notable individuals across fields such as entertainment, sports, and academia.
  • E. Bentley
    Bentley is a former coal mining town in South Yorkshire, England, historically associated with the Yorkshire coalfield.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d7948888190b59ddc7061d13e84 completed April 19, 2026, 9:16 a.m.
Created at: April 10, 2026, 10:18 a.m.