Triple
T16864787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corrour railway station |
E410009
|
entity |
| Predicate | railwayAuthorityCategory |
P27767
|
FINISHED |
| Object | DfT category F2 station |
—
|
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: DfT category F2 station | Statement: [Corrour railway station, railwayAuthorityCategory, DfT category F2 station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railwayAuthorityCategory Context triple: [Corrour railway station, railwayAuthorityCategory, DfT category F2 station]
-
A.
railwayStationCategory
chosen
Indicates the classification or type category assigned to a railway station within a rail network or system.
-
B.
railwayClass
Indicates the specific classification or category assigned to a railway or railway service within a defined system.
-
C.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
-
D.
hasNationalRailCategory
Indicates that an entity is assigned a specific classification or category within a national rail system.
-
E.
railwayUse
Indicates that something is used as, or functions in the capacity of, a railway or rail-based transportation facility.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b506dd1c81909ab8006b6a1e2b7a |
completed | April 18, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.