Triple
T12701288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bundesstraße |
E303466
|
entity |
| Predicate | routeNumberColor |
P9560
|
FINISHED |
| Object | black on yellow background |
—
|
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: black on yellow background | Statement: [Bundesstraße, routeNumberColor, black on yellow background]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeNumberColor Context triple: [Bundesstraße, routeNumberColor, black on yellow background]
-
A.
hasRouteColorStandard
chosen
Indicates that a route is associated with a standardized color designation used for identification or classification.
-
B.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
C.
networkColorOfLine
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
-
D.
mapColor_RedLine
Indicates that a map element is represented or highlighted using a red line.
-
E.
roadUniformColor
Indicates that the entire road surface shares a single, consistent color throughout.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d962a32c6481908ddaddae4ea267bf |
completed | April 10, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69d960be63f081908a5ef5ef17a311bf |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:22 p.m.