Triple
T4295513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westminster Underground Station |
E99700
|
entity |
| Predicate | hasTravelcardZone |
P49359
|
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: [Westminster Underground Station, hasTravelcardZone, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTravelcardZone Context triple: [Westminster Underground Station, hasTravelcardZone, 1]
-
A.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
B.
hasFareZoneFeature
Indicates that an entity is associated with a specific fare zone or fare-related area designation.
-
C.
hasFarePaidArea
Indicates that an entity includes or is associated with a zone where access is restricted to users who have paid a fare.
-
D.
hasFormerFareZone
Indicates that an entity was previously assigned to a particular fare zone, but is no longer in that fare zone.
-
E.
hasFareZoneCode
chosen
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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35085b864819086cf726285384566 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.