Triple
T11348638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N’djili International Airport |
E268783
|
entity |
| Predicate | handlesCargoTraffic |
P99377
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [N’djili International Airport, handlesCargoTraffic, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handlesCargoTraffic Context triple: [N’djili International Airport, handlesCargoTraffic, yes]
-
A.
hasCargoTrafficLevel
Indicates the intensity or volume of cargo-related traffic associated with an entity, such as a route, location, or transport facility.
-
B.
hasCargoTrafficType
Indicates that an entity is associated with a specific type or category of cargo traffic it handles or supports.
-
C.
hasPassengerTrafficFrom
Indicates that an entity receives or handles passenger traffic originating from another entity.
-
D.
freightTraffic
Indicates the movement or volume of goods and cargo being transported, typically via commercial transport networks such as rail, road, sea, or air.
-
E.
handlesMostPassengerTrafficOf
Indicates that one entity is responsible for managing the largest share of passenger traffic associated with another entity, compared to all similar entities.
- F. None of above. chosen
Provenance (4 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80148e2048190a716b515d78efdd1 |
completed | April 9, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69d7e6f8aeb4819080476f16a69b2ee3 |
completed | April 9, 2026, 5:50 p.m. |
| PDg | Predicate description generation | batch_69d801451b1c8190944b17906b354142 |
completed | April 9, 2026, 7:43 p.m. |
Created at: April 8, 2026, 9:33 p.m.