Triple
T6285993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C-8 |
E140901
|
entity |
| Predicate | hasColorRepresentation |
P48842
|
FINISHED |
| Object | specific line color on Cercanías Madrid maps |
—
|
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: specific line color on Cercanías Madrid maps | Statement: [C-8, hasColorRepresentation, specific line color on Cercanías Madrid maps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorRepresentation Context triple: [C-8, hasColorRepresentation, specific line color on Cercanías Madrid maps]
-
A.
hasColorModel
Indicates that an entity uses or is associated with a particular color representation model (such as RGB, CMYK, or HSV) for defining its colors.
-
B.
hasColorType
Indicates that an entity is associated with a specific category or type of color.
-
C.
hasColorInfo
chosen
Indicates that an entity is associated with specific color-related information or attributes.
-
D.
hasColorSymbol
Indicates that one entity is associated with another entity that serves as its representative or symbolic color.
-
E.
hasColorReference
Indicates that one entity serves as a reference or source for determining or specifying the color associated with another 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063fe59fc81908dbd968017771190 |
completed | March 22, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69c0560a0270819098ad2785b91e8f39 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:26 p.m.