Triple
T11301839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 鳳翔 |
E267612
|
entity |
| Predicate | airGroupTypical |
P4683
|
FINISHED |
| Object | around 15–20 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: around 15–20 aircraft | Statement: [鳳翔, airGroupTypical, around 15–20 aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airGroupTypical Context triple: [鳳翔, airGroupTypical, around 15–20 aircraft]
-
A.
airGroupType
Indicates the classification or category of an air group based on its role, composition, or operational function.
-
B.
airGroup
Indicates a relationship where entities are grouped or organized together based on their association with air or aerial operations.
-
C.
airGroupComplement
Indicates that one air group serves as a complement or supporting component to another air group within a larger operational structure.
-
D.
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).
-
E.
airService
Indicates that an air transportation service (such as flights or air routes) is provided or operates between the related entities.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a4aad4819097384e1b591be2e3 |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787a6ca2c8190afdc24b61ccd3f8a |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.