Triple
T36906312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finnish national road 19 |
E912786
|
entity |
| Predicate | hasRouteNumberSignTextColor |
P50027
|
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: [Finnish national road 19, hasRouteNumberSignTextColor, white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteNumberSignTextColor Context triple: [Finnish national road 19, hasRouteNumberSignTextColor, white]
-
A.
hasRouteColorStandard
Indicates that a route is associated with a standardized color designation used for identification or classification.
-
B.
roadSignColor
chosen
Indicates the color attribute associated with a particular road sign.
-
C.
hasColorOnRouteMap
Indicates that a specific color is used to represent an entity (such as a route or line) on a route map.
-
D.
hasNationalSignageColor
Indicates that an entity uses a particular color (or set of colors) as its officially designated national signage color scheme.
-
E.
railwaySignColor
Indicates the color attribute assigned to a particular railway sign.
- 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_69f76e879768819085c2fb31a6a5b44b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fed09a12648190affcd9bacf7ca275 |
completed | May 9, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69fecf91d6f481908deb60c965c433ed |
completed | May 9, 2026, 6:09 a.m. |
Created at: May 3, 2026, 4:13 p.m.