Triple
T8473428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buenos Aires bus network |
E200332
|
entity |
| Predicate | typicalPassenger |
P15253
|
FINISHED |
| Object | commuters |
—
|
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: commuters | Statement: [Buenos Aires bus network, typicalPassenger, commuters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPassenger Context triple: [Buenos Aires bus network, typicalPassenger, commuters]
-
A.
passengers
Indicates that one entity is traveling in or being transported by another entity, typically as a non-operating occupant.
-
B.
hasPassengerRole
chosen
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
-
C.
typicalProfile
Indicates that an entity represents the standard or most representative profile or pattern for another entity.
-
D.
typicalBoardingPriority
Indicates the usual order or precedence in which different groups of passengers are allowed to board.
-
E.
typicalSeat
Indicates the usual or standard seating position or location associated with an entity in a given context.
- 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4f4fbf481909e4fd7c078b27477 |
completed | March 31, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:11 p.m.