Triple
T8554080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NS Sprinter |
E202518
|
entity |
| Predicate | railwayCodeWithinNS |
P71744
|
FINISHED |
| Object | Sprinter category |
—
|
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: Sprinter category | Statement: [NS Sprinter, railwayCodeWithinNS, Sprinter category]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayCodeWithinNS Context triple: [NS Sprinter, railwayCodeWithinNS, Sprinter category]
-
A.
railroadCodeFor
Indicates that a specific railroad code is assigned to or used to identify a particular railroad entity.
-
B.
networkRailRouteCode
chosen
Indicates that a specific Network Rail route code is assigned to or associated with an entity, identifying the rail route it belongs to or operates on.
-
C.
railwayName
Indicates the name assigned to a specific railway or railway line in the relationship.
-
D.
railwayStationCodeFor
Indicates that one entity is the designated railway station code corresponding to a particular railway station.
-
E.
railwayLineNumber
Indicates the identifying number assigned to a specific railway line within a rail 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe8894e7c8190bc0ae2ceec473ecb |
completed | March 31, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69cbd1160fcc8190aa380a73610af731 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:19 p.m.