Triple
T23334713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SC |
E591544
|
entity |
| Predicate | standardPlateType |
P7361
|
FINISHED |
| Object | civilian vehicles |
—
|
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: civilian vehicles | Statement: [SC, standardPlateType, civilian vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardPlateType Context triple: [SC, standardPlateType, civilian vehicles]
-
A.
plateType
chosen
Indicates the specific category or style of plate associated with an item or context.
-
B.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
C.
standardPar
Indicates that two entities are parallel and conform to a recognized or defined standard of parallelism.
-
D.
standardParallelType
Indicates the type or method by which the standard parallel(s) are defined or specified in a coordinate reference or map projection system.
-
E.
standardSetSize
Indicates that there is a defined or typical number of elements that constitute the standard size for a given set.
- 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_69e25d20156c81908c5c53195bd9c738 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f197f08fe481908766e674164d6d45 |
completed | April 29, 2026, 5:32 a.m. |
| PD | Predicate disambiguation | batch_69effcf8ca2c8190887d4f4656617d21 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:16 p.m.