Triple
T15767149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nigeria LNG plant at Bonny Island |
E382250
|
entity |
| Predicate | designCapacityLNG |
P11312
|
FINISHED |
| Object | about 22 million tonnes per annum |
—
|
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: about 22 million tonnes per annum | Statement: [Nigeria LNG plant at Bonny Island, designCapacityLNG, about 22 million tonnes per annum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designCapacityLNG Context triple: [Nigeria LNG plant at Bonny Island, designCapacityLNG, about 22 million tonnes per annum]
-
A.
unitCapacity
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
-
B.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
C.
launcherCapacity
Indicates the maximum number or size of items that a launcher is designed to hold or deploy.
-
D.
fuelCapacityKg
Indicates the maximum amount of fuel an entity can hold, measured in kilograms.
-
E.
installedCapacity
chosen
Indicates the maximum output or production capability that has been set up or built for a system, facility, or equipment, typically measured under specified conditions.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e051951bac8190a7d45f3612c6de72 |
completed | April 16, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.