Triple

T13525771
Position Surface form Disambiguated ID Type / Status
Subject Toyota performance models E323012 entity
Predicate marketedAs P1395 FINISHED
Object GR models
GR models are Toyota’s high-performance, motorsport-inspired vehicles developed by its Gazoo Racing division.
 E1044601 NE FINISHED

How this triple was built (4 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: GR models | Statement: [Toyota performance models, marketedAs, GR models]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GR models
Context triple: [Toyota performance models, marketedAs, GR models]
  • A. GRG
    GRG is the standard abbreviation for the Grand Rapids Griffins, a professional ice hockey team in the American Hockey League.
  • B. GR70
    GR70 is a long-distance hiking trail in France, famously following the route taken by writer Robert Louis Stevenson through the Cévennes region.
  • C. GR-61
    GR-61 is the ISO 3166-2 subdivision code assigned to the Pieria regional unit in Greece.
  • D. GVRA
    GVRA is a state agency in Georgia that provides vocational rehabilitation and related services to help individuals with disabilities prepare for, obtain, and maintain employment.
  • E. GLMR
    GLMR is the ICAO airport code assigned to Spriggs Payne Airport in Monrovia, Liberia.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: GR models
Triple: [Toyota performance models, marketedAs, GR models]
Generated description
GR models are Toyota’s high-performance, motorsport-inspired vehicles developed by its Gazoo Racing division.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GR models
Target entity description: GR models are Toyota’s high-performance, motorsport-inspired vehicles developed by its Gazoo Racing division.
  • A. GRG
    GRG is the standard abbreviation for the Grand Rapids Griffins, a professional ice hockey team in the American Hockey League.
  • B. GR70
    GR70 is a long-distance hiking trail in France, famously following the route taken by writer Robert Louis Stevenson through the Cévennes region.
  • C. GR-61
    GR-61 is the ISO 3166-2 subdivision code assigned to the Pieria regional unit in Greece.
  • D. GVRA
    GVRA is a state agency in Georgia that provides vocational rehabilitation and related services to help individuals with disabilities prepare for, obtain, and maintain employment.
  • E. GLMR
    GLMR is the ICAO airport code assigned to Spriggs Payne Airport in Monrovia, Liberia.
  • F. None of above. chosen

Provenance (5 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa6ad60819087824e4ac83934ed completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7549dda6481908e9305690488b1af completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f7555173d08190be887e81c148192e completed May 3, 2026, 2:01 p.m.
NED2 Entity disambiguation (via description) batch_69f75675df788190b4aa562fe0bc1d75 completed May 3, 2026, 2:06 p.m.
Created at: April 9, 2026, 9:44 p.m.