Triple
T35424227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whimple railway station |
E1023874
|
entity |
| Predicate | passengerInformation |
P40049
|
FINISHED |
| Object | automated announcements |
—
|
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: automated announcements | Statement: [Whimple railway station, passengerInformation, automated announcements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerInformation Context triple: [Whimple railway station, passengerInformation, automated announcements]
-
A.
publicPassengerService
Indicates that an entity provides transportation services that are available to the general public for carrying passengers.
-
B.
usedForPassengerInformation
chosen
Indicates that something serves the purpose of providing information to passengers.
-
C.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
D.
passengerFlight
Indicates a relationship where a flight is specifically operated to transport passengers rather than cargo or other purposes.
-
E.
passengerSystem
Indicates a relationship where an entity functions as or belongs to a passenger-related system (such as a transport or service system designed for 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f795905ed88190a9c6573824a56ca9 |
completed | May 3, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.