Triple
T15635165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kandos railway station |
E375922
|
entity |
| Predicate | servedPassengerServices |
P31751
|
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: [Kandos railway station, servedPassengerServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedPassengerServices Context triple: [Kandos railway station, servedPassengerServices, yes]
-
A.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
B.
majorPassengerService
Indicates that a transportation facility or route provides primary or significant passenger service as one of its main functions.
-
C.
formerPassengerService
Indicates that an entity previously provided passenger transportation services but no longer does so.
-
D.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
-
E.
operatedPassengerServices
chosen
Indicates that an entity provided and managed transportation services specifically for carrying passengers.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb8b4c48190b80fea6877483089 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.