Triple
T14023189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 空母「赤城」 |
E337386
|
entity |
| Predicate | 搭載機数 |
P90293
|
FINISHED |
| Object | 約90機 |
—
|
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: 約90機 | Statement: [空母「赤城」, 搭載機数, 約90機]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 搭載機数 Context triple: [空母「赤城」, 搭載機数, 約90機]
-
A.
aircraftTypesCarried
Indicates that one entity (typically a vessel, facility, or platform) carries or is capable of carrying specific types of aircraft as part of its operations or configuration.
-
B.
usesCarrierAircraft
Indicates that one entity employs or operates aircraft that are designed to be launched from and recovered by an aircraft carrier.
-
C.
fuselageCount
Indicates the number of fuselages associated with or contained in an aircraft or aerospace structure.
-
D.
airWingCapacity
chosen
Indicates the maximum number or volume of aircraft or air operations that an air wing can support or handle.
-
E.
paratroopCapacity
Indicates the maximum number of paratroopers or amount of airborne troops that something (typically a vehicle or vessel) is capable of carrying or deploying.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2f3d87b88190b038d334f4965369 |
completed | April 14, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69de05a802ac819090604025aae6a4d5 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:19 p.m.