Triple
T32558466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pursuit Special |
E832154
|
entity |
| Predicate | propUsage |
P2529
|
FINISHED |
| Object | multiple stunt and hero cars built |
—
|
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: multiple stunt and hero cars built | Statement: [Pursuit Special, propUsage, multiple stunt and hero cars built]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: propUsage Context triple: [Pursuit Special, propUsage, multiple stunt and hero cars built]
-
A.
propUsed
Indicates that a particular property or attribute is utilized or applied in a given context or situation.
-
B.
usesProp
Indicates that one entity employs, utilizes, or makes use of a particular property, resource, or object in performing an action or fulfilling a function.
-
C.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
D.
exportUse
Indicates that something is used, intended, or suitable for export from one place or market to another.
-
E.
promotesUseIn
Indicates that one entity actively encourages, supports, or increases the adoption or application of another entity within a particular context or setting.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c60206e48190b5139a3ad31330bc |
completed | May 3, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:03 a.m.