Triple

T2462569
Position Surface form Disambiguated ID Type / Status
Subject Toyota Highlander E54565 entity
Predicate alsoKnownAs P39 FINISHED
Object Toyota Kluger
The Toyota Kluger is a mid-size crossover SUV produced by Toyota, marketed in various regions as a comfortable, family-oriented vehicle with three-row seating.
E268327 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: Toyota Kluger | Statement: [Toyota Highlander, alsoKnownAs, Toyota Kluger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyota Kluger
Context triple: [Toyota Highlander, alsoKnownAs, Toyota Kluger]
  • A. Isuzu
    Isuzu is a Japanese automotive manufacturer best known for producing commercial vehicles, pickup trucks, and diesel engines for global markets.
  • B. Hino
    Hino is a town in Shiga Prefecture, Japan, known for its historical streetscapes and traditional industries.
  • C. Hino
    Hino is a city in western Tokyo, Japan, known as a residential and industrial suburb within the Tama area.
  • D. Toyota Verblitz
    Toyota Verblitz is a professional Japanese rugby union team based in Toyota, Aichi, competing in Japan Rugby League One and known for attracting high-profile international players.
  • E. Mitsubishi
    Mitsubishi is a major Japanese multinational conglomerate known for its diverse businesses in industries such as automotive, heavy industry, finance, and electronics.
  • 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: Toyota Kluger
Triple: [Toyota Highlander, alsoKnownAs, Toyota Kluger]
Generated description
The Toyota Kluger is a mid-size crossover SUV produced by Toyota, marketed in various regions as a comfortable, family-oriented vehicle with three-row seating.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Toyota Kluger
Target entity description: The Toyota Kluger is a mid-size crossover SUV produced by Toyota, marketed in various regions as a comfortable, family-oriented vehicle with three-row seating.
  • A. Isuzu
    Isuzu is a Japanese automotive manufacturer best known for producing commercial vehicles, pickup trucks, and diesel engines for global markets.
  • B. Hino
    Hino is a town in Shiga Prefecture, Japan, known for its historical streetscapes and traditional industries.
  • C. Hino
    Hino is a city in western Tokyo, Japan, known as a residential and industrial suburb within the Tama area.
  • D. Toyota Verblitz
    Toyota Verblitz is a professional Japanese rugby union team based in Toyota, Aichi, competing in Japan Rugby League One and known for attracting high-profile international players.
  • E. Mitsubishi
    Mitsubishi is a major Japanese multinational conglomerate known for its diverse businesses in industries such as automotive, heavy industry, finance, and electronics.
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd11f093c8190877db3026d430bd5 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0d561a081909310113658b98f12 completed March 9, 2026, 4:09 p.m.
NEDg Description generation batch_69aef8380d24819092b6502117a8ed42 completed March 9, 2026, 4:41 p.m.
NED2 Entity disambiguation (via description) batch_69aef936b86c81908573ea73314fe6a9 completed March 9, 2026, 4:45 p.m.
Created at: March 6, 2026, 9:44 p.m.