Triple
T29400941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichthys gas field |
E745638
|
entity |
| Predicate | LPGCapacity_MTPA |
P166738
|
FINISHED |
| Object | approximately 1.65 |
—
|
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 1.65 | Statement: [Ichthys gas field, LPGCapacity_MTPA, approximately 1.65]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LPGCapacity_MTPA Context triple: [Ichthys gas field, LPGCapacity_MTPA, approximately 1.65]
-
A.
fuelCapacityKg
Indicates the maximum amount of fuel an entity can hold, measured in kilograms.
-
B.
fuelCapacityLiters
Indicates the amount of fuel a vehicle or container can hold, measured in liters.
-
C.
typeOfGasUsed
Indicates the specific kind of gas that is utilized in relation to an entity or process.
-
D.
hasBackupDieselCapacityApprox
Indicates that an entity possesses an approximate amount of backup diesel-powered capacity available for use.
-
E.
designCapacityLNGWithTrain7
Indicates the liquefied natural gas (LNG) design production capacity specifically associated with train 7 of a facility.
- 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_69f0a79eb7d081908c67197a5f347e68 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66a0772648190b5083f0fa099137c |
completed | May 2, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69f660f4f7a88190b93c60d76b86c912 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661b47d088190934f63884a203261 |
completed | May 2, 2026, 8:42 p.m. |
Created at: April 28, 2026, 2:50 p.m.