Triple
T7817122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DF |
E181037
|
entity |
| Predicate | plateFormatContext |
P7361
|
FINISHED |
| Object | Mercosur-style Brazilian 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: Mercosur-style Brazilian license plates | Statement: [DF, plateFormatContext, Mercosur-style Brazilian license plates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plateFormatContext Context triple: [DF, plateFormatContext, Mercosur-style Brazilian license plates]
-
A.
plate3
Indicates that one entity is a third plate or dish associated with, supporting, or serving another entity in a given context.
-
B.
projectionFormat
Indicates the specific technical format or method used to project visual content (such as film or digital media) onto a display surface.
-
C.
plateType
chosen
Indicates the specific category or style of plate associated with an item or context.
-
D.
plate
Indicates that one entity serves as a plate or flat dish used to hold, support, or present another entity.
-
E.
plateName
Indicates the name or label assigned to a specific plate.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf96ea6d881908eff5f750e0f6700 |
completed | March 30, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:39 p.m.