Triple
T25822389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Severe Threat Level |
E650436
|
entity |
| Predicate | scaleMembers |
P160288
|
FINISHED |
| Object | High Threat Level |
—
|
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: High Threat Level | Statement: [Severe Threat Level, scaleMembers, High Threat Level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scaleMembers Context triple: [Severe Threat Level, scaleMembers, High Threat Level]
-
A.
scaleMembers
chosen
Indicates adjusting the size, number, or magnitude of members in a group or collection according to some scaling factor or rule.
-
B.
scaleProperty
Indicates that one entity defines or modifies the scale, magnitude, or proportional sizing used to interpret or represent a property of another entity.
-
C.
scaleRelation
Indicates a relationship where one quantity, object, or representation is proportionally larger or smaller than another according to a specific scale or factor.
-
D.
scaleFunction
Indicates a relationship where one entity defines how another entity’s values are proportionally adjusted or transformed according to a scaling rule or factor.
-
E.
scalingProperty
Indicates how a quantity or behavior changes in proportion to changes in another variable, typically under resizing or rescaling conditions.
- 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_69e7ab367fcc8190a5ff1e7f3da046a4 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 22, 2026, 7:30 a.m.