Triple
T26780890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quebec Autoroute system |
E670242
|
entity |
| Predicate | hasSignageTextColor |
P37450
|
FINISHED |
| Object | white |
—
|
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: white | Statement: [Quebec Autoroute system, hasSignageTextColor, white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignageTextColor Context triple: [Quebec Autoroute system, hasSignageTextColor, white]
-
A.
signageTextColor
chosen
Indicates the color used for the text displayed on a sign.
-
B.
hasNationalSignageColor
Indicates that an entity uses a particular color (or set of colors) as its officially designated national signage color scheme.
-
C.
usesSignageColorSystem
Indicates that an entity employs a specific color-based signage system to convey information, instructions, or guidance.
-
D.
hasSignageName
Indicates that an entity has a specific name or label as it appears on its physical signage.
-
E.
hasSignageType
Indicates the specific category or kind of signage associated with an object, location, or entity.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 27, 2026, 4:09 a.m.