Triple
T14580604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese aircraft carrier Shinano |
E342181
|
entity |
| Predicate | designedAircraftCapacity |
P90293
|
FINISHED |
| Object | approximately 40–50 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: approximately 40–50 aircraft | Statement: [Japanese aircraft carrier Shinano, designedAircraftCapacity, approximately 40–50 aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedAircraftCapacity Context triple: [Japanese aircraft carrier Shinano, designedAircraftCapacity, approximately 40–50 aircraft]
-
A.
aircraftCapacity
Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
-
B.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
C.
aircraftPanCapacity
Indicates the maximum number of passengers an aircraft is designed or allowed to carry.
-
D.
airWingCapacity
chosen
Indicates the maximum number or volume of aircraft or air operations that an air wing can support or handle.
-
E.
appliedToAircraftDesignedBy
Indicates that something (such as a component, system, or regulation) is applied to an aircraft that was designed by a specified designer or organization.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f6f78c81908a30ecb4c025299d |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.