Triple
T26716848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jane station |
E673589
|
entity |
| Predicate | fareCollector |
P1740
|
FINISHED |
| Object | TTC staff |
—
|
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: TTC staff | Statement: [Jane station, fareCollector, TTC staff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareCollector Context triple: [Jane station, fareCollector, TTC staff]
-
A.
fareCollectionType
Indicates the method or system used to collect fares or payments for a service.
-
B.
fareSystem
Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
-
C.
fare
Indicates the price or cost required for a person or thing to be transported by a particular mode of travel or service.
-
D.
fareContext
Indicates the pricing or fare-related conditions under which a transaction, service, or travel arrangement is applied.
-
E.
fareControl
chosen
Indicates that an entity is responsible for monitoring, enforcing, or managing payment of fares for access to a service or facility.
- 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_69eecda3a22881908f3061c760b9d542 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 3:38 a.m.