Triple
T18152743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Asakai |
E434547
|
entity |
| Predicate | approximateShipsDestroyed |
P821
|
FINISHED |
| Object | hundreds of ships |
—
|
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: hundreds of ships | Statement: [Battle of Asakai, approximateShipsDestroyed, hundreds of ships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateShipsDestroyed Context triple: [Battle of Asakai, approximateShipsDestroyed, hundreds of ships]
-
A.
tonnageSunk
Indicates the amount of a vessel’s weight or cargo capacity that has been destroyed or sunk, typically measured in tons.
-
B.
battleshipsDamaged
Indicates that one or more battleships have sustained damage, typically as a result of combat or hostile action.
-
C.
fleetDestroyedBy
Indicates that a fleet was destroyed as a direct result of actions taken by another specified entity.
-
D.
shipwrecksDestroyedIn
Indicates that one or more shipwrecks were destroyed within a specified location or during a particular event or time period.
-
E.
shipsSunkOrTotalLoss
chosen
Indicates that the referenced ships were sunk or otherwise rendered a total loss (permanently unusable).
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de39a8f481908d1752767d0aae0e |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.