Triple
T29727293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dießen railway station |
E752216
|
entity |
| Predicate | hasPassengerInformationDisplay |
P192227
|
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: [Dießen railway station, hasPassengerInformationDisplay, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerInformationDisplay Context triple: [Dießen railway station, hasPassengerInformationDisplay, yes]
-
A.
hasPassengerInformationSystem
Indicates that an entity is equipped with a system that provides information to passengers, such as schedules, announcements, or travel updates.
-
B.
usedForPassengerInformation
Indicates that something serves the purpose of providing information to passengers.
-
C.
hasDepartureScreens
Indicates that a location or facility is equipped with screens displaying departure information for services such as trains, buses, or flights.
-
D.
hasTimetableInformationDisplays
chosen
Indicates that an entity is equipped with displays that present timetable or schedule information.
-
E.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
- 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fdb31800508190beec15adb9bbd292 |
completed | May 8, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69fdb19c381c8190bafb2f565da097f1 |
completed | May 8, 2026, 9:49 a.m. |
Created at: April 28, 2026, 7:40 p.m.