Triple
T69628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunfermline Queen Margaret railway station |
E1391
|
entity |
| Predicate | hasPassengerServices |
P1298
|
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: [Dunfermline Queen Margaret railway station, hasPassengerServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerServices Context triple: [Dunfermline Queen Margaret railway station, hasPassengerServices, yes]
-
A.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
B.
hasFerryService
Indicates that there is an operational ferry connection or transport service available between the related locations or entities.
-
C.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
D.
hasGroundTransportation
chosen
Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
-
E.
hasTransportationSystem
Indicates that an entity possesses, operates, or is served by an organized system for transporting people or goods.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.