Triple
T94643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tornado Alley (southern and central parts) |
E1901
|
entity |
| Predicate | emergencyPreparednessFocus |
P2534
|
FINISHED |
| Object | tornado warnings |
—
|
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: tornado warnings | Statement: [Tornado Alley (southern and central parts), emergencyPreparednessFocus, tornado warnings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emergencyPreparednessFocus Context triple: [Tornado Alley (southern and central parts), emergencyPreparednessFocus, tornado warnings]
-
A.
policyFocus
Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
-
B.
epicenter
Indicates the central point or focal location from which an event, influence, or effect originates or is most intensely experienced.
-
C.
civilianImpact
Indicates the extent to which an action, event, or situation affects civilians, especially in terms of harm, disruption, or other consequences.
-
D.
preparesFor
chosen
Indicates that one entity is used, designed, or undertaken in order to get another entity ready for a future event, state, or activity.
-
E.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
- 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.