Triple
T33502946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urquinaona station |
E858043
|
entity |
| Predicate | hasLineColorForL4 |
P34402
|
FINISHED |
| Object | yellow |
—
|
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: yellow | Statement: [Urquinaona station, hasLineColorForL4, yellow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLineColorForL4 Context triple: [Urquinaona station, hasLineColorForL4, yellow]
-
A.
isColorCodedLine
Indicates that a line is represented or distinguished using specific colors according to a coding scheme.
-
B.
fourthStripeColor
Indicates that a subject has a fourth stripe whose color is specified by the related object.
-
C.
hasTrimLineColor
Indicates that an entity has a specific color applied to the trim or outline portion of its visual representation.
-
D.
hasLRTLine
Indicates that a location, station, or area is served by or lies along a specific light rail transit (LRT) line.
-
E.
networkColorOfLine
chosen
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
- 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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: May 1, 2026, 1:38 a.m.