Triple
T26486710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taiho-class aircraft carrier |
E664840
|
entity |
| Predicate | hasHangarType |
P22186
|
FINISHED |
| Object | enclosed hangar |
—
|
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: enclosed hangar | Statement: [Taiho-class aircraft carrier, hasHangarType, enclosed hangar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHangarType Context triple: [Taiho-class aircraft carrier, hasHangarType, enclosed hangar]
-
A.
hasHangarCount
Indicates the number of hangars associated with or contained by an entity.
-
B.
hasHangars
chosen
Indicates that one entity possesses or contains hangars used for housing aircraft or similar vehicles.
-
C.
hasBlueImpulseHangar
Indicates that an entity possesses or is associated with a blue-colored hangar designated for impulse-related operations or storage.
-
D.
hasCargoHold
Indicates that something possesses a dedicated space or compartment for storing or transporting cargo.
-
E.
hasCargoDoorVariant
Indicates that one entity is a specific cargo-door-equipped version or configuration variant of another entity.
- 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_69ee883bc85481909885f92415cbce33 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f612ff24a48190aad3b4a3d2d81c98 |
completed | May 2, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 12:31 a.m.