Triple

T27687629
Position Surface form Disambiguated ID Type / Status
Subject Wolseley E698073 entity
Predicate finalModelsBasedOn P88131 FINISHED
Object Austin 1100/1300
The Austin 1100/1300 was a popular British family car of the 1960s and early 1970s, known for its front-wheel-drive layout and badge-engineered variants across several BMC marques.
 E1784490 NE FINISHED

How this triple was built (3 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: Austin 1100/1300 | Statement: [Wolseley, finalModelsBasedOn, Austin 1100/1300]
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: Austin 1100/1300
Triple: [Wolseley, finalModelsBasedOn, Austin 1100/1300]
Generated description
The Austin 1100/1300 was a popular British family car of the 1960s and early 1970s, known for its front-wheel-drive layout and badge-engineered variants across several BMC marques.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: finalModelsBasedOn
Context triple: [Wolseley, finalModelsBasedOn, Austin 1100/1300]
  • A. testedModel
    Indicates that an entity has evaluated or examined a particular model to assess its performance, behavior, or validity.
  • B. coverModelSelection
    Indicates selecting or designating a particular model to appear on the cover of a publication or media item.
  • C. possibleModel
    Indicates that one entity can serve as a potential or candidate model or template for another entity.
  • D. modelIn
    Indicates that one entity serves as a representation or simulation of another entity.
  • E. adoptedModel chosen
    Indicates that one entity has formally chosen, accepted, or implemented another entity as its preferred model or standard.
  • F. None of above.

Provenance (6 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_69ef590df8708190af5488f0638e790c completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f74c70fd248190a9d5543afcb08211 completed May 3, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12dab19e148190a7265456accbb535 completed May 24, 2026, 11:02 a.m.
NEDg Description generation batch_6a12dcb81e7c8190aff8806c7d06e8d7 completed May 24, 2026, 11:10 a.m.
NED2 Entity disambiguation (via description) batch_6a12dd3ba39481909149d5d9eb7dd5eb completed May 24, 2026, 11:12 a.m.
PD Predicate disambiguation batch_69f7478e3b548190a51d5d436e2bb036 completed May 3, 2026, 1:03 p.m.
Created at: April 27, 2026, 2:50 p.m.