Triple
T27687629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolseley |
E698073
|
entity |
| Predicate | finalModelsBasedOn |
P88131
|
FINISHED |
| Object | Austin 1100/1300 |
—
|
NE NERFINISHED |
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: Austin 1100/1300 | Statement: [Wolseley, finalModelsBasedOn, Austin 1100/1300]
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 (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_69ef590df8708190af5488f0638e790c |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 27, 2026, 2:50 p.m.