Triple
T20859345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Stan |
E513572
|
entity |
| Predicate | wasDeadly |
P142136
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hurricane Stan, wasDeadly, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasDeadly Context triple: [Hurricane Stan, wasDeadly, true]
-
A.
deadliestIn
Indicates that something has the highest lethality or causes the most deaths within a specified context, group, or location.
-
B.
wasLeftForDeadBy
Indicates that one entity abandoned another in a life-threatening situation, assuming or intending that the abandoned entity would die.
-
C.
willKill
Indicates that one entity is destined or intends to cause the death of another entity in the future.
-
D.
fatallyDamaged
Indicates that an entity has been harmed or impaired to such an extent that death is inevitable or has already occurred as a result of the damage.
-
E.
deathBefore
Indicates that one entity’s death occurred earlier in time than another entity’s death.
- F. None of above. chosen
Provenance (4 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_69e0b4f5b01081909452f654d2fc3f50 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3aabef4819098f0fd24dcc27dbd |
completed | April 21, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a593f481908beb457c29f1ce73 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:44 p.m.