Triple
T75103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akagi |
E1501
|
entity |
| Predicate | causeOfLoss |
P694
|
FINISHED |
| Object | bomb damage from U.S. Navy aircraft |
—
|
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: bomb damage from U.S. Navy aircraft | Statement: [Akagi, causeOfLoss, bomb damage from U.S. Navy aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfLoss Context triple: [Akagi, causeOfLoss, bomb damage from U.S. Navy aircraft]
-
A.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
B.
economicDamage
Indicates that one entity causes or experiences financial loss, harm, or negative economic impact as a result of another entity or event.
-
C.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
D.
affectedAgency
Indicates that one entity has an effect on, or causes a change in, the agency or capacity for action of another entity.
-
E.
damageYear
Indicates the year in which the damage to an entity occurred or was recorded.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25314bd6c81908d1cfd4b83f20049 |
completed | Feb. 28, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69a24eae77ec81909015906f31f2b62e |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.