Triple
T3554871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Clair station |
E75194
|
entity |
| Predicate | farePaidZone |
P39868
|
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: [St. Clair station, farePaidZone, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: farePaidZone Context triple: [St. Clair station, farePaidZone, yes]
-
A.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
B.
hasFarePaidArea
chosen
Indicates that an entity includes or is associated with a zone where access is restricted to users who have paid a fare.
-
C.
hasFareZoneFeature
Indicates that an entity is associated with a specific fare zone or fare-related area designation.
-
D.
hasFareZoneCode
Indicates that an entity is associated with a specific fare zone identifier used for pricing or tariff purposes.
-
E.
fareSystem
Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
- 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_69ad85d45090819086f34fb85d850a1e |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc05549d88190acdebdd542ea1a67 |
completed | March 8, 2026, 6:30 p.m. |
| PD | Predicate disambiguation | batch_69adb83270ac819083967db0570167d2 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:20 p.m.