Triple

T16068312
Position Surface form Disambiguated ID Type / Status
Subject Toyota Motor Manufacturing Kenya E389791 entity
Predicate headquartersLocation P62 FINISHED
Object Kenya E11292 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: Kenya | Statement: [Toyota Motor Manufacturing Kenya, headquartersLocation, Kenya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kenya
Context triple: [Toyota Motor Manufacturing Kenya, headquartersLocation, Kenya]
  • A. Kenya chosen
    Kenya is an East African country known for its diverse wildlife, scenic landscapes from savannas to highlands, and a coastline along the Indian Ocean.
  • B. Nyeri, Kenya
    Nyeri, Kenya is a town in central Kenya near the Aberdare Range, known for its colonial-era history, agricultural economy, and as the final resting place of Scouting founder Robert Baden-Powell.
  • C. Kamba (Kenya)
    Kamba (Kenya) is a Bantu language spoken primarily by the Kamba people in eastern Kenya.
  • D. Uganda
    Uganda is a landlocked country in East Africa known for its diverse landscapes, abundant wildlife, and location along the equator.
  • E. Kenie
    Kenie is an alternative spelling of the given name Kenny, typically used as a personal name.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183bb98c88190ae4b5773358078be completed April 17, 2026, 12:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb8f12708190956f203a3e58e18b completed May 10, 2026, 2:21 a.m.
Created at: April 10, 2026, 4:57 a.m.