Triple
T2336422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiryū-class aircraft carrier |
E44319
|
entity |
| Predicate | airGroupRole |
P38296
|
FINISHED |
| Object | fleet air arm base |
—
|
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: fleet air arm base | Statement: [Hiryū-class aircraft carrier, airGroupRole, fleet air arm base]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airGroupRole Context triple: [Hiryū-class aircraft carrier, airGroupRole, fleet air arm base]
-
A.
airGroupType
Indicates the classification or category of an air group based on its role, composition, or operational function.
-
B.
airGroupSize
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).
-
C.
addressesRole
Indicates that one entity directs communication, content, or action specifically toward another entity in its capacity or function as a particular role.
-
D.
roleInTeamViewer
Indicates the specific function, position, or responsibility an entity holds within a TeamViewer-related team or collaborative setup.
-
E.
hasSubsidiaryRoleInGroup
Indicates that an entity holds a secondary or supporting role within a specified group.
- F. None of above. chosen
Provenance (4 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6f75d888190a2e41edaa532e83f |
completed | March 7, 2026, 6:34 a.m. |
| PD | Predicate disambiguation | batch_69abc594087c819098100a10c5478a4b |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6f4245881909282b3184a288e2a |
completed | March 7, 2026, 6:34 a.m. |
Created at: March 4, 2026, 7:51 p.m.