Triple
T127864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaga |
E2588
|
entity |
| Predicate | airGroupSizeEarlyWar |
P4683
|
FINISHED |
| Object | about 90 aircraft |
—
|
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 90 aircraft | Statement: [Kaga, airGroupSizeEarlyWar, about 90 aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airGroupSizeEarlyWar Context triple: [Kaga, airGroupSizeEarlyWar, about 90 aircraft]
-
A.
airGroupSize
chosen
Indicates the number of units or elements grouped together in an air-related context (such as aircraft in a formation or air assets in an operation).
-
B.
airGroupCommanderAttacker
Indicates that the subject serves as the commanding officer of an air group that is carrying out an attack.
-
C.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
D.
troopStrengthAlliedApprox
Indicates that the approximate troop strength of one entity is being assessed or reported in relation to its allied forces.
-
E.
combatantStrength
Indicates the relative level of power, capability, or effectiveness one combatant has in a conflict or confrontation compared to others.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25763ccf8819094e8dffb2ff98480 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564c11208190ad25495609d94d87 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.