Triple
T2814248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of the Sibuyan Sea |
E54244
|
entity |
| Predicate | primaryJapaneseShipType |
P3141
|
FINISHED |
| Object | battleship |
—
|
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: battleship | Statement: [Battle of the Sibuyan Sea, primaryJapaneseShipType, battleship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryJapaneseShipType Context triple: [Battle of the Sibuyan Sea, primaryJapaneseShipType, battleship]
-
A.
involvedShipJapan
Indicates that a ship associated with Japan was involved in the referenced event or activity.
-
B.
shipClass
chosen
Indicates the classification or type category to which a particular ship belongs.
-
C.
originalShipType
Indicates the type or category of ship that an entity was originally classified or built as.
-
D.
statusOfOtherShips
Indicates the relationship that reports or reflects the current conditions or states (such as position, readiness, or operational status) of other ships.
-
E.
notableShip
Indicates that there is a notable or significant ship associated with the subject 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde4ba34c819085a336498fc326b0 |
completed | March 7, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.