Triple
T24604215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MS |
E608916
|
entity |
| Predicate | codeUsedOn |
P2367
|
FINISHED |
| Object | vehicle license plates |
—
|
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: vehicle license plates | Statement: [MS, codeUsedOn, vehicle license plates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeUsedOn Context triple: [MS, codeUsedOn, vehicle license plates]
-
A.
usedOn
chosen
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
B.
toolUsed
Indicates that an action or task is performed using a particular tool as the means or instrument.
-
C.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
D.
designationUsedFor
Indicates that a particular name, label, or title is employed to refer to or identify a specific entity or role.
-
E.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
- 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_69e2c4d060e08190ac9f7c49b1036e20 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:31 a.m.