Triple
T8796306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nossa Senhora da Paz metro station |
E209296
|
entity |
| Predicate | hasAutomaticFareCollection |
P85441
|
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: [Nossa Senhora da Paz metro station, hasAutomaticFareCollection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAutomaticFareCollection Context triple: [Nossa Senhora da Paz metro station, hasAutomaticFareCollection, yes]
-
A.
hasFareControlIntegrationSince
Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
-
B.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
-
C.
fareSystem
Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
-
D.
airTrainFareCollection
Indicates a relationship where fares for an air train service are collected from passengers or through a designated payment system.
-
E.
hasAutomaticTrainControlCompatibility
Indicates that an entity is compatible with, or supports integration with, an automatic train control (ATC) system.
- F. None of above. chosen
Provenance (4 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa24ca08190a7738a7f1c446456 |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1d48f08190b325a77d4c76d223 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:44 p.m.