Triple
T37212975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS White Plains (CVE-66) |
E922657
|
entity |
| Predicate | engagedEnemyTypeAtBattleOffSamar |
P47243
|
FINISHED |
| Object | Japanese battleships |
—
|
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: Japanese battleships | Statement: [USS White Plains (CVE-66), engagedEnemyTypeAtBattleOffSamar, Japanese battleships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engagedEnemyTypeAtBattleOffSamar Context triple: [USS White Plains (CVE-66), engagedEnemyTypeAtBattleOffSamar, Japanese battleships]
-
A.
opponentAtSurigaoStrait
Indicates that one entity was the opposing force of another in the Battle of Surigao Strait.
-
B.
engagedEnemyShips
chosen
Indicates that one or more entities have actively attacked, exchanged fire with, or otherwise entered into direct combat with enemy ships.
-
C.
finalEngagementOpponentShip
Indicates that a ship is the opposing vessel faced in the final engagement or battle.
-
D.
navalEngagementType
Indicates the specific kind or category of naval combat or maritime military engagement involved in the relationship.
-
E.
auxiliaryTroopsFoughtIn
Indicates that auxiliary troops participated as combatants in a particular battle or military conflict.
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.