Triple
T20943866
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winchcombe railway station |
E515792
|
entity |
| Predicate | hasSidings |
P18851
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Winchcombe railway station, hasSidings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSidings Context triple: [Winchcombe railway station, hasSidings, yes]
-
A.
hasTurnbackSidings
Indicates that a railway line, route, or station includes sidings specifically used for turning back or reversing trains.
-
B.
hasSidePlatformCount
Indicates the number of side platforms associated with an entity, such as a station or stop.
-
C.
hasRailYard
chosen
Indicates that one entity possesses, contains, or includes a rail yard as part of its facilities or infrastructure.
-
D.
hasParkingLotOnBothSidesOfTracks
Indicates that there are parking lots located on both sides of the railway tracks at a given location.
-
E.
hasSidePlatforms
Indicates that something is equipped with platforms located on its sides, typically for access, support, or operation.
- 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f95838708190978dfa8bc786fb22 |
completed | April 21, 2026, 4:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c9b1bae48190a845165fed1b005e |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:50 p.m.