Triple
T15391973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Ball Ferry Line |
E368066
|
entity |
| Predicate | vehicleCapacityApprox |
P46451
|
FINISHED |
| Object | 110 vehicles |
—
|
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: 110 vehicles | Statement: [Black Ball Ferry Line, vehicleCapacityApprox, 110 vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleCapacityApprox Context triple: [Black Ball Ferry Line, vehicleCapacityApprox, 110 vehicles]
-
A.
transportCapacity
Indicates the maximum quantity of people, goods, or materials that can be transported by an entity or system within a given operation or time frame.
-
B.
cargoCapacityFeature
chosen
Indicates that an entity has a feature specifying how much cargo it can carry or accommodate.
-
C.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
D.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
-
E.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e7838b48190862b43c6c8620692 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.