Triple
T3723783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STIB/MIVB Brussels fare zone |
E81699
|
entity |
| Predicate | mainTariffAreaFor |
P82
|
FINISHED |
| Object | Brussels urban public transport |
—
|
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: Brussels urban public transport | Statement: [STIB/MIVB Brussels fare zone, mainTariffAreaFor, Brussels urban public transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainTariffAreaFor Context triple: [STIB/MIVB Brussels fare zone, mainTariffAreaFor, Brussels urban public transport]
-
A.
hasPrimaryServiceArea
Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
-
B.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
-
C.
areaServed
chosen
Indicates the geographic region or jurisdiction within which a service, organization, or activity is provided or applicable.
-
D.
venueArea
Indicates the physical size or spatial extent of a venue, typically measured in units such as square meters or square feet.
-
E.
regulatesArea
Indicates that one entity exercises control or governance over the spatial extent, scope, or domain of another entity.
- 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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcaf3f2ec8190a3a8f363cfb762f3 |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc0436e508190909ec4a3e8443aef |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.