Triple
T12832479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RJ-14 |
E306821
|
entity |
| Predicate | plateColorForCommercialVehicles |
P107131
|
FINISHED |
| Object | yellow background with black letters |
—
|
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: yellow background with black letters | Statement: [RJ-14, plateColorForCommercialVehicles, yellow background with black letters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plateColorForCommercialVehicles Context triple: [RJ-14, plateColorForCommercialVehicles, yellow background with black letters]
-
A.
colorOfTrailMarkings
Indicates the relationship specifying what color the trail’s markings are.
-
B.
liveryColors
Indicates the specific set of colors used as the official or characteristic color scheme associated with an entity (such as a brand, organization, or vehicle).
-
C.
trunkColorDesignation
Indicates the specified color assigned to the trunk of an object (such as a tree or similar structure).
-
D.
rollingStockColor
Indicates the color attribute assigned to a piece of rolling stock (such as a rail vehicle) in the relationship.
-
E.
coneColor
Indicates that one entity is the color attribute assigned to a cone-shaped object.
- F. None of above. chosen
Provenance (4 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9713e45a88190acd346f066093550 |
completed | April 10, 2026, 9:53 p.m. |
Created at: April 9, 2026, 5:34 p.m.