Triple
T20943867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winchcombe railway station |
E515792
|
entity |
| Predicate | hasCarriageShed |
P141787
|
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, hasCarriageShed, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarriageShed Context triple: [Winchcombe railway station, hasCarriageShed, yes]
-
A.
hasCarriageWorks
Indicates that one entity possesses, operates, or is associated with facilities where railway carriages are designed, built, or maintained in relation to another entity.
-
B.
hasCarriage
Indicates that one entity possesses, is equipped with, or is accompanied by a carriage associated with it.
-
C.
hasTrailerCar
Indicates that one vehicle is connected to and pulling another vehicle configured as a trailer car.
-
D.
hasUndercarriageType
Indicates the specific type or configuration of undercarriage that an object (typically a vehicle or machine) possesses.
-
E.
carriageType
Indicates the specific kind or category of carriage associated with or used in relation to an entity.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69e5d53d22d08190bc17ed4bed53804a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:50 p.m.