Triple
T94642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tornado Alley (southern and central parts) |
E1901
|
entity |
| Predicate | hasHazard |
P1950
|
FINISHED |
| Object | EF3 to EF5 tornadoes |
—
|
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: EF3 to EF5 tornadoes | Statement: [Tornado Alley (southern and central parts), hasHazard, EF3 to EF5 tornadoes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHazard Context triple: [Tornado Alley (southern and central parts), hasHazard, EF3 to EF5 tornadoes]
-
A.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
susceptibleTo
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
-
C.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
D.
hasConsequence
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
E.
hasCause
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24ebb3da08190a8b82564f33cde3b |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.