Triple
T7440162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese carrier Taiho |
E171727
|
entity |
| Predicate | damageMechanism |
P22116
|
FINISHED |
| Object | internal gasoline vapor explosion |
—
|
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: internal gasoline vapor explosion | Statement: [Japanese carrier Taiho, damageMechanism, internal gasoline vapor explosion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageMechanism Context triple: [Japanese carrier Taiho, damageMechanism, internal gasoline vapor explosion]
-
A.
killMechanism
Indicates the method or process by which one entity causes the death or destruction of another.
-
B.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
C.
primaryDamageType
chosen
Indicates the main kind of harm or injury that an action, event, or object is responsible for causing.
-
D.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
E.
damageAdjusted
Indicates that the amount of damage has been modified from its original value, typically to account for mitigating or amplifying factors.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34d84008190936af2b3670ef210 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.