Triple
T26810351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kemsing railway station |
E671971
|
entity |
| Predicate | hasPenaltyFaresScheme |
P175307
|
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: [Kemsing railway station, hasPenaltyFaresScheme, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPenaltyFaresScheme Context triple: [Kemsing railway station, hasPenaltyFaresScheme, yes]
-
A.
supportsTransitDiscounts
Indicates that an entity provides or enables discounted fares or pricing for public transit services.
-
B.
fareAppliesTo
Indicates that a specific fare is applicable to a particular trip, service, passenger category, or travel condition.
-
C.
hasCurrencyOfFares
Indicates the currency in which fares or prices for transportation or services are denominated.
-
D.
fareSurchargeApplies
Indicates that an additional charge is applied on top of the standard fare for a given trip or service.
-
E.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
- F. None of above. chosen
Provenance (4 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_69eeb3225a3c8190aaf6746efeded2f3 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6d1d916f881909575c2b22c416a5b |
completed | May 3, 2026, 4:40 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
| PDg | Predicate description generation | batch_69f6d0d331dc8190be5aa6bfc6365e67 |
completed | May 3, 2026, 4:36 a.m. |
Created at: April 27, 2026, 4:29 a.m.