Triple
T21391190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Street station |
E527652
|
entity |
| Predicate | hasTravelcardZoneBoundary |
P105131
|
FINISHED |
| Object | between Zone 1 and Zone 2 |
—
|
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: between Zone 1 and Zone 2 | Statement: [Old Street station, hasTravelcardZoneBoundary, between Zone 1 and Zone 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTravelcardZoneBoundary Context triple: [Old Street station, hasTravelcardZoneBoundary, between Zone 1 and Zone 2]
-
A.
locatedInTravelcardZoneBoundary
Indicates that something lies on or within the defined boundary of a specific travelcard fare zone.
-
B.
hasFareBoundary
chosen
Indicates that there is a defined limit or border beyond which a particular fare, ticket, or pricing rule no longer applies.
-
C.
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.
-
D.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
E.
fareZoneIncludes
Indicates that a specified fare zone geographically or logically contains a given location, stop, or segment for fare calculation purposes.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b113690c81909c0a378fddba5d3a |
completed | April 22, 2026, 11:29 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:13 p.m.