Triple
T20894606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wengen railway station |
E514498
|
entity |
| Predicate | hasLuggageServices |
P30409
|
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: [Wengen railway station, hasLuggageServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLuggageServices Context triple: [Wengen railway station, hasLuggageServices, yes]
-
A.
hasBaggageService
chosen
Indicates that an entity provides or supports services related to handling, storing, or managing baggage for others.
-
B.
hasLuggage
Indicates that an entity is carrying, possessing, or associated with one or more pieces of luggage.
-
C.
hasCargoServices
Indicates that an entity provides or is equipped to handle cargo transportation or freight services for another entity or location.
-
D.
hasPassengerAirlineService
Indicates that a location or facility is served by scheduled passenger airline flights.
-
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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6d06129788190b88ab807af4641c1 |
completed | April 21, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:47 p.m.