Triple
T7719543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leicester Square station |
E174970
|
entity |
| Predicate | isInContactlessFareZone |
P75854
|
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: [Leicester Square station, isInContactlessFareZone, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInContactlessFareZone Context triple: [Leicester Square station, isInContactlessFareZone, yes]
-
A.
hasNearbyPass
Indicates that an entity has at least one pass (e.g., transit or access pass) available within a short or locally defined distance from it.
-
B.
isWithinLondonFareSystem
chosen
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.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
D.
hasFareZoneFeature
Indicates that an entity is associated with a specific fare zone or fare-related area designation.
-
E.
hasFarePaidArea
Indicates that an entity includes or is associated with a zone where access is restricted to users who have paid a fare.
- 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702eedc088190be645c029dfc462a |
completed | March 27, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69c701683dec8190be9861e592aa8ce0 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:05 p.m.