Triple
T38487052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Gilbert |
E917945
|
entity |
| Predicate | damageUSD_adjusted |
P66042
|
FINISHED |
| Object | over 10000000000 |
—
|
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: over 10000000000 | Statement: [Hurricane Gilbert, damageUSD_adjusted, over 10000000000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageUSD_adjusted Context triple: [Hurricane Gilbert, damageUSD_adjusted, over 10000000000]
-
A.
damageAdjusted
chosen
Indicates that the amount of damage has been modified from its original value, typically to account for mitigating or amplifying factors.
-
B.
damageCostNote
Indicates a descriptive note or explanation associated with the cost of damage, providing contextual or clarifying information about that damage-related expense.
-
C.
currencyOfDamageCost
Indicates the monetary currency in which a specified damage cost amount is expressed.
-
D.
economicDamageApprox
Indicates that one entity has caused or is associated with an estimated or approximate amount of economic damage to another entity or system.
-
E.
damageAmount
Indicates the quantity or extent of damage inflicted, suffered, or associated with an entity or event.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdaa36f90819093f8661969990c7d |
completed | May 7, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69fcd8fefc588190b063d7ea1ec87b07 |
completed | May 7, 2026, 6:25 p.m. |
Created at: May 3, 2026, 4:31 p.m.