Triple
T21208441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilmington Oil Field |
E522651
|
entity |
| Predicate | approximateOriginalOilInPlace |
P10552
|
FINISHED |
| Object | over 3 billion barrels |
—
|
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: over 3 billion barrels | Statement: [Wilmington Oil Field, approximateOriginalOilInPlace, over 3 billion barrels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateOriginalOilInPlace Context triple: [Wilmington Oil Field, approximateOriginalOilInPlace, over 3 billion barrels]
-
A.
approximateEstimation
Indicates an estimation relationship where one value or assessment is only roughly or closely, but not exactly, equal to another.
-
B.
estimatedUsing
Indicates that one entity’s value, state, or outcome is derived by applying an estimation method, model, or procedure based on another entity.
-
C.
hasEstimatedOriginalVolume
chosen
Indicates that an entity is associated with an approximate or calculated value for its original volume.
-
D.
refiningCapacityBarrelsPerDayApprox
Indicates the approximate amount of crude oil a refinery can process, measured in barrels per day.
-
E.
firstOil
Indicates that the subject is the first entity to discover, produce, or commercially extract oil in relation to the object (such as a region, field, or context).
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73436eb4c819082e05caf1ba52672 |
completed | April 21, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:25 p.m.