Triple

T21532193
Position Surface form Disambiguated ID Type / Status
Subject Arnold Clark E531256 entity
Predicate sellsBrand P38689 FINISHED
Object Nissan 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: Nissan | Statement: [Arnold Clark, sellsBrand, Nissan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nissan
Context triple: [Arnold Clark, sellsBrand, Nissan]
  • A. Nissan
    Nissan is a river in southwestern Sweden that flows through the province of Halland before reaching the Kattegat.
  • B. Nissan chosen
    Nissan is a major Japanese automobile manufacturer known for producing a wide range of passenger cars, trucks, and electric vehicles sold globally.
  • C. Mitsubishi Motors
    Mitsubishi Motors is a Japanese automotive manufacturer known for producing a wide range of passenger cars, SUVs, and light commercial vehicles and for its involvement in global automotive alliances.
  • D. Mitsubishi
    Mitsubishi is a major Japanese multinational conglomerate known for its diverse businesses in industries such as automotive, heavy industry, finance, and electronics.
  • E. Datsun
    Datsun is a historic Japanese automobile brand, revived as a budget-focused marque under the Renault–Nissan–Mitsubishi Alliance and known for its small, affordable cars.
  • 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_69e0c45e5b8881908ac18fc2f493b114 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee9d0a0e7c8190bbb7ed5c4dfe33af completed April 26, 2026, 11:17 p.m.
Created at: April 16, 2026, 6:27 p.m.