Triple
T24668308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2011 Joplin tornado |
E610747
|
entity |
| Predicate | damageRating |
P156947
|
FINISHED |
| Object | EF5 |
—
|
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: EF5 | Statement: [2011 Joplin tornado, damageRating, EF5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: damageRating Context triple: [2011 Joplin tornado, damageRating, EF5]
-
A.
damageBasis
Indicates the underlying reason, cause, or basis on which damage is determined or assessed in a given context.
-
B.
damageEffect
Indicates that one entity causes harm, reduction, or deterioration to another entity or its properties.
-
C.
damageClass
Indicates the type or category of damage associated with an action, event, or interaction between entities.
-
D.
damageDescription
Indicates a textual description of the nature, extent, or characteristics of damage associated with an entity or event.
-
E.
damageScaling
Indicates how the amount of damage changes in proportion to certain factors, such as level, stats, or conditions.
- 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_69e2c4d505cc8190981881df06c0bf52 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f41010f06c81908ee7f773220df14f |
completed | May 1, 2026, 2:29 a.m. |
Created at: April 18, 2026, 2:41 a.m.