Triple
T12638526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moor Park |
E301828
|
entity |
| Predicate | hasFareBoundaryRole |
P105131
|
FINISHED |
| Object | boundary between Travelcard zones 6 and 7 |
—
|
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: boundary between Travelcard zones 6 and 7 | Statement: [Moor Park, hasFareBoundaryRole, boundary between Travelcard zones 6 and 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFareBoundaryRole Context triple: [Moor Park, hasFareBoundaryRole, boundary between Travelcard zones 6 and 7]
-
A.
hasFareBoundary
chosen
Indicates that there is a defined limit or border beyond which a particular fare, ticket, or pricing rule no longer applies.
-
B.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
C.
hasBoundaryStations
Indicates that an entity is associated with specific stations that mark its boundary or endpoints.
-
D.
hasFareGateConnectionTo
Indicates that there is a direct passage or connection between two areas that is controlled or mediated by fare gates.
-
E.
hasFareZoneCode
Indicates that an entity is associated with a specific fare zone identifier used for pricing or tariff 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_69d7bdec9f9c8190b4bac675b7588211 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:16 p.m.