Triple
T33353878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westcombe Park railway station |
E854016
|
entity |
| Predicate | hasLondonFareIntegration |
P177118
|
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: [Westcombe Park railway station, hasLondonFareIntegration, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLondonFareIntegration Context triple: [Westcombe Park railway station, hasLondonFareIntegration, yes]
-
A.
hasFareIntegration
chosen
Indicates that two or more transportation services or systems share a coordinated fare structure, allowing passengers to use a single ticket or payment arrangement across them.
-
B.
isWithinLondonFareSystem
Indicates that an entity (such as a station, stop, or route) is located inside the area covered by the London public transport fare system.
-
C.
hasFareControlIntegrationSince
Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
-
D.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
-
E.
hasLondonOvergroundPlatforms
Indicates that the subject has platforms specifically served by the London Overground rail network.
- 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_69f3496acbc8819099fd0305ecc42080 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
Created at: May 1, 2026, 1:34 a.m.