Triple
T11938496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Bismarck Sea |
E284112
|
entity |
| Predicate | shipsSunkJapanese |
P98360
|
FINISHED |
| Object | 8 transport 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: 8 transport ships | Statement: [Battle of the Bismarck Sea, shipsSunkJapanese, 8 transport ships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipsSunkJapanese Context triple: [Battle of the Bismarck Sea, shipsSunkJapanese, 8 transport ships]
-
A.
reasonForSinking
Indicates the cause or circumstance that led to something sinking.
-
B.
involvedShipJapan
Indicates that a ship associated with Japan was involved in the referenced event or activity.
-
C.
shipTypeSunk
chosen
Indicates that a particular type of ship has been sunk as a result of some event or action.
-
D.
tonnageSunk
Indicates the amount of a vessel’s weight or cargo capacity that has been destroyed or sunk, typically measured in tons.
-
E.
sunkBy
Indicates that one entity (typically a vessel or structure) was caused to sink or be destroyed in water by another entity.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903415d2481909d84e6727454b9fe |
completed | April 10, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.