Triple
T29255182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Car (first class) |
E741684
|
entity |
| Predicate | railwayClassColor |
P48066
|
FINISHED |
| Object | green |
—
|
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: green | Statement: [Green Car (first class), railwayClassColor, green]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayClassColor Context triple: [Green Car (first class), railwayClassColor, green]
-
A.
railwayClass
Indicates the specific classification or category assigned to a railway or railway service within a defined system.
-
B.
railwaySignColor
Indicates the color attribute assigned to a particular railway sign.
-
C.
rollingStockColor
chosen
Indicates the color attribute assigned to a piece of rolling stock (such as a rail vehicle) in the relationship.
-
D.
railroadClass
Indicates the classification or category of a railroad according to an established system (e.g., by size, revenue, or regulatory status).
-
E.
railwayOperatorBranding
Indicates that one entity is responsible for the railway-related branding, livery, or visual identity applied to another entity (such as a train service, station, or rolling stock).
- 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_69f0911eba2c8190b07cd2fdf91422c9 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 28, 2026, 12:36 p.m.