Triple
T534258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battleship Row, Pearl Harbor |
E12291
|
entity |
| Predicate | resultOfAttack |
P374
|
FINISHED |
| Object | sinking of USS Arizona (BB-39) |
—
|
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: sinking of USS Arizona (BB-39) | Statement: [Battleship Row, Pearl Harbor, resultOfAttack, sinking of USS Arizona (BB-39)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resultOfAttack Context triple: [Battleship Row, Pearl Harbor, resultOfAttack, sinking of USS Arizona (BB-39)]
-
A.
attackedIn
Indicates that one entity carried out an attack in the location, context, or time frame specified by another entity or value.
-
B.
defenseResult
Indicates the outcome or consequence of a defensive action or strategy in response to an attack or threat.
-
C.
attackType
Indicates the specific method, style, or category of attack used in an aggressive or hostile action between entities.
-
D.
mainAttacker
Indicates that an entity is the primary or leading aggressor responsible for initiating or carrying out an attack against another entity.
-
E.
result
chosen
Indicates that one entity is produced, caused, or brought about as an outcome or consequence of another entity or process.
- 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_69a4933208e88190891f5debab1b776d |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b3e49081909810fa417b31306f |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.