Triple
T2869235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Street Kensington Underground station |
E63516
|
entity |
| Predicate | isWithinTravelcardZone |
P844
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [High Street Kensington Underground station, isWithinTravelcardZone, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isWithinTravelcardZone Context triple: [High Street Kensington Underground station, isWithinTravelcardZone, 1]
-
A.
hasFareZone
chosen
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
B.
hasFarePaidArea
Indicates that an entity includes or is associated with a zone where access is restricted to users who have paid a fare.
-
C.
hasRailwayZone
Indicates that a location or railway entity falls under the jurisdiction or coverage area of a specific railway zone.
-
D.
hasFormerFareZone
Indicates that an entity was previously assigned to a particular fare zone, but is no longer in that fare zone.
-
E.
isWithinPark
Indicates that one entity is located inside the boundaries of a park that contains it.
- 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_69ab4c42fb8c8190b36e161d47c03b81 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdfe15ff081908dd1dad62c292b2b |
completed | March 7, 2026, 8:20 a.m. |
| PD | Predicate disambiguation | batch_69abdd142e4c8190b424cb0c5ff40d04 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.