Triple
T32350461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J-45 |
E826578
|
entity |
| Predicate | hasElectronicsOption |
P88194
|
FINISHED |
| Object | factory-installed pickup system |
—
|
LITERAL FINISHED |
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: factory-installed pickup system | Statement: [J-45, hasElectronicsOption, factory-installed pickup system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasElectronicsOption Context triple: [J-45, hasElectronicsOption, factory-installed pickup system]
-
A.
hasElectronicsFeature
chosen
Indicates that an entity possesses or is characterized by a specific electronic-related feature or capability.
-
B.
isElectronicOnly
Indicates that the item or resource exists solely in digital form and is not available in any physical format.
-
C.
hasRetailOption
Indicates that one entity offers, includes, or is associated with a particular retail option (such as a sales channel, purchase method, or retail configuration) for another entity.
-
D.
hasElectronicEffect
Indicates that one entity exerts or contributes an electronic influence or effect on another entity within a specified context.
-
E.
isMechanicalOrElectronic
Indicates that something operates using mechanical components, electronic components, or a combination of both.
- 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_69f34914dfc48190a390cd0720d9e86f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
Created at: May 1, 2026, 12:49 a.m.