Triple
T35790635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Nimitz Carrier Strike Group |
E1034682
|
entity |
| Predicate | typicalDestroyerType |
P109622
|
FINISHED |
| Object | Arleigh Burke-class guided-missile destroyer |
E589254
|
NE 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: Arleigh Burke-class guided-missile destroyer | Statement: [USS Nimitz Carrier Strike Group, typicalDestroyerType, Arleigh Burke-class guided-missile destroyer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDestroyerType Context triple: [USS Nimitz Carrier Strike Group, typicalDestroyerType, Arleigh Burke-class guided-missile destroyer]
-
A.
typicalShipStrength
Indicates the usual or characteristic level of strength or power associated with a given ship.
-
B.
fleetDestroyedBy
Indicates that a fleet was destroyed as a direct result of actions taken by another specified entity.
-
C.
shipTypeSunk
Indicates that a particular type of ship has been sunk as a result of some event or action.
-
D.
submarineClassName
Indicates the specific class designation or type category to which a submarine belongs.
-
E.
typicalShipTypes
chosen
Indicates that the subject is commonly or characteristically associated with the specified types or categories of ships.
- F. None of above.
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_69f76e1575908190aaa306d843b41c14 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a389c0fc75081908e7da549f4147825 |
completed | June 22, 2026, 2:21 a.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.