Triple
T18796472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GM N-body platform |
E459646
|
entity |
| Predicate | usedInApplicationType |
P96491
|
FINISHED |
| Object | passenger cars |
—
|
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: passenger cars | Statement: [GM N-body platform, usedInApplicationType, passenger cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInApplicationType Context triple: [GM N-body platform, usedInApplicationType, passenger cars]
-
A.
hasApplicationType
chosen
Indicates that an entity is associated with or classified by a specific type or category of application.
-
B.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
C.
typeOfApplication
Indicates the specific category or kind of application involved in the relationship or action.
-
D.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
E.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a01ed3c08190890d9518ed69fdee |
completed | April 20, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.