Triple

T2160481
Position Surface form Disambiguated ID Type / Status
Subject Isuzu E47989 entity
Predicate hasModel P2390 FINISHED
Object Isuzu Elf
The Isuzu Elf is a line of light-duty commercial trucks produced by Japanese manufacturer Isuzu, widely used for urban delivery and utility applications.
E248744 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: Isuzu Elf | Statement: [Isuzu, hasModel, Isuzu Elf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isuzu Elf
Context triple: [Isuzu, hasModel, Isuzu Elf]
  • A. Nissan NV400
    The Nissan NV400 is a large light commercial van developed in partnership with Renault and Opel/Vauxhall, sharing its platform with the Renault Master.
  • 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. Fiat Ducato
    The Fiat Ducato is a popular light commercial van produced by Fiat, widely used across Europe for cargo transport, camper conversions, and other utility purposes.
  • E. Peugeot Boxer
    The Peugeot Boxer is a large light commercial van produced by the French automaker Peugeot, widely used for cargo transport, passenger shuttles, and camper conversions.
  • 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: Isuzu Elf
Triple: [Isuzu, hasModel, Isuzu Elf]
Generated description
The Isuzu Elf is a line of light-duty commercial trucks produced by Japanese manufacturer Isuzu, widely used for urban delivery and utility applications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Isuzu Elf
Target entity description: The Isuzu Elf is a line of light-duty commercial trucks produced by Japanese manufacturer Isuzu, widely used for urban delivery and utility applications.
  • A. Nissan NV400
    The Nissan NV400 is a large light commercial van developed in partnership with Renault and Opel/Vauxhall, sharing its platform with the Renault Master.
  • 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. Fiat Ducato
    The Fiat Ducato is a popular light commercial van produced by Fiat, widely used across Europe for cargo transport, camper conversions, and other utility purposes.
  • E. Peugeot Boxer
    The Peugeot Boxer is a large light commercial van produced by the French automaker Peugeot, widely used for cargo transport, passenger shuttles, and camper conversions.
  • 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_69a88a1d1fd8819088b34990d69a712f completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbe8894d481908eda9363fd36fea6 completed March 7, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6af04e908190a8eaee7500e0b1af completed March 9, 2026, 6:38 a.m.
NEDg Description generation batch_69ae6b9da51c819085beb79a14f5d8b5 completed March 9, 2026, 6:41 a.m.
NED2 Entity disambiguation (via description) batch_69ae6c2a465c8190a9fe2a465e9ac3f0 completed March 9, 2026, 6:43 a.m.
Created at: March 4, 2026, 7:45 p.m.