Triple

T625425
Position Surface form Disambiguated ID Type / Status
Subject Toyota Tundra E15807 entity
Predicate brand P1500 FINISHED
Object Toyota E13136 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: Toyota | Statement: [Toyota Tundra, brand, Toyota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyota
Context triple: [Toyota Tundra, brand, Toyota]
  • A. Toyota Motor Corporation chosen
    Toyota Motor Corporation is a Japanese multinational automaker renowned for its reliable vehicles, pioneering of lean manufacturing and the Toyota Production System, and global leadership in hybrid technology.
  • B. Nissan
    Nissan is a major Japanese automobile manufacturer known for producing a wide range of passenger cars, trucks, and electric vehicles sold globally.
  • C. Honda
    Honda is a major Japanese automobile and motorcycle manufacturer known for its reliable, fuel-efficient vehicles and global market presence.
  • D. Subaru
    Subaru is the Japanese name for the Pleiades star cluster, often associated with unity and prominently used as the brand name and logo motif of a major Japanese automobile manufacturer.
  • E. Ford
    Ford is a common English surname borne by numerous notable individuals, including U.S. President Gerald Ford.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e574444819087999404f3e3ffd9 completed March 1, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a56935ec748190984b9cb6add6b700 completed March 2, 2026, 10:40 a.m.
Created at: March 1, 2026, 7:35 p.m.