Triple
T10769797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TMB 3000 series |
E254043
|
entity |
| Predicate | hasPassengerAreas |
P30403
|
FINISHED |
| Object | saloon with longitudinal seating |
—
|
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: saloon with longitudinal seating | Statement: [TMB 3000 series, hasPassengerAreas, saloon with longitudinal seating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerAreas Context triple: [TMB 3000 series, hasPassengerAreas, saloon with longitudinal seating]
-
A.
hasPassengerArea
chosen
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
B.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
-
C.
hasPassengerServicesTo
Indicates that a transportation provider operates passenger services connecting one location or entity to another.
-
D.
hasBusBays
Indicates that a location or facility is equipped with one or more designated bus bays for buses to stop, load, or unload passengers.
-
E.
hasPassengerInformationSystem
Indicates that an entity is equipped with a system that provides information to passengers, such as schedules, announcements, or travel updates.
- 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_69d6aa5f54f4819082d0bbcb6f8797e6 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d732307fb88190ba1447f68523c58a |
completed | April 9, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69d6f311529c819080ca5493d55d6050 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:16 p.m.