Triple
T35054296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natuna D-Alpha gas field |
E1011417
|
entity |
| Predicate | hasCO2Content |
P31410
|
FINISHED |
| Object | about 70 percent |
—
|
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 70 percent | Statement: [Natuna D-Alpha gas field, hasCO2Content, about 70 percent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCO2Content Context triple: [Natuna D-Alpha gas field, hasCO2Content, about 70 percent]
-
A.
canBeCarbonated
Indicates that the subject is capable of being made carbonated, typically by dissolving carbon dioxide under pressure.
-
B.
carbonateContent
Indicates the proportion or amount of carbonate present in a given material or sample.
-
C.
hasTypicalCarbonContentRange
Indicates the usual lower and upper bounds of carbon content typically found in or associated with an entity.
-
D.
carbonDioxideLevel
chosen
Indicates the measured concentration or amount of carbon dioxide present in a given environment or system.
-
E.
hasCarbonatedWater
Indicates that an entity contains or is associated with carbonated (fizzy) water as a component or ingredient.
- 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_69f76dd09c308190a523454853ce842b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.