Triple
T19260869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IMB |
E481645
|
entity |
| Predicate | tankVolume |
P13057
|
FINISHED |
| Object | approximately 8 kilotons of water |
—
|
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 8 kilotons of water | Statement: [IMB, tankVolume, approximately 8 kilotons of water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tankVolume Context triple: [IMB, tankVolume, approximately 8 kilotons of water]
-
A.
volumeOf
Indicates the quantitative three-dimensional space occupied by an entity or contained within an object.
-
B.
waterVolume
chosen
Indicates the amount of water present in or associated with an entity, typically measured as a volume.
-
C.
mainTankCapacity
Indicates the maximum volume of fuel or liquid that the primary tank is designed to hold.
-
D.
cargoHoldVolume
Indicates the total internal volume available within a cargo hold for storing goods or materials.
-
E.
unitCapacity
Indicates the maximum quantity or load that a single unit is designed or allowed to hold, process, or accommodate.
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb890e7c8190beba407f63459382 |
completed | April 20, 2026, 10:10 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:28 p.m.