Triple
T24885913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Komandorski Islands |
E622849
|
entity |
| Predicate | JapaneseShipInvolved |
P681
|
FINISHED |
| Object | Abukuma |
—
|
NE NERFINISHED |
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: Abukuma | Statement: [Battle of the Komandorski Islands, JapaneseShipInvolved, Abukuma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JapaneseShipInvolved Context triple: [Battle of the Komandorski Islands, JapaneseShipInvolved, Abukuma]
-
A.
involvedShipJapan
chosen
Indicates that a ship associated with Japan was involved in the referenced event or activity.
-
B.
JapaneseDestroyersDamaged
Indicates that one or more Japanese destroyer-class ships have sustained damage.
-
C.
reasonForSinking
Indicates the cause or circumstance that led to something sinking.
-
D.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
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_69e2fac4aa848190b3446a3922cec150 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cf017a88190b4985b11159c907d |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 5:25 a.m.