Triple
T34893370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Buses route 134 |
E1006361
|
entity |
| Predicate | colourOnTubeMap |
P69958
|
FINISHED |
| Object | red |
—
|
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: red | Statement: [London Buses route 134, colourOnTubeMap, red]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colourOnTubeMap Context triple: [London Buses route 134, colourOnTubeMap, red]
-
A.
mapColor
Indicates a relationship where a map region or area is assigned or associated with a specific color, typically for visualization or categorization purposes.
-
B.
mapColorBrownLine
Indicates that an entity is associated with the brown-colored line on a map (e.g., a transit or route line depicted in brown).
-
C.
hasColorOnRouteMap
chosen
Indicates that a specific color is used to represent an entity (such as a route or line) on a route map.
-
D.
mapColorOrangeLine
Indicates that an entity is associated with, represented by, or rendered using the color of the orange line on a map.
-
E.
mapColor_RedLine
Indicates that a map element is represented or highlighted using a red line.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.