Triple
T34975471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIPS 199 |
E1008664
|
entity |
| Predicate | impactDimension |
P51728
|
FINISHED |
| Object | confidentiality |
—
|
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: confidentiality | Statement: [FIPS 199, impactDimension, confidentiality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactDimension Context triple: [FIPS 199, impactDimension, confidentiality]
-
A.
impactFeatureName
Indicates that one entity has an effect on, or causes a change in, a specific feature or characteristic identified by name in another entity or context.
-
B.
impactCategory
chosen
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
C.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
D.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
-
E.
impactLevel
Indicates the degree or intensity of effect that one entity, action, or event has on another.
- 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_69f76dc78a308190a1ac29ad4a9a4895 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:01 p.m.