Triple
T3665493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M/V Columbia |
E77748
|
entity |
| Predicate | capacityVehicles |
P18218
|
FINISHED |
| Object | approximately 130 |
—
|
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: approximately 130 | Statement: [M/V Columbia, capacityVehicles, approximately 130]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityVehicles Context triple: [M/V Columbia, capacityVehicles, approximately 130]
-
A.
cargoCapacityFeature
Indicates that an entity has a feature specifying how much cargo it can carry or accommodate.
-
B.
designedCargoCapacity
chosen
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
C.
cargoSpace
Indicates that one entity provides storage capacity or room for carrying goods, equipment, or other items for another entity.
-
D.
maximumPassengerCapacity
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
E.
cargoVehicle
Indicates a relationship where a vehicle is used or designated for transporting cargo or goods.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc400352081908c16a6a7670eb52a |
completed | March 8, 2026, 6:46 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:25 p.m.