Triple
T34975474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIPS 199 |
E1008664
|
entity |
| Predicate | impactAssessmentCriterion |
P96882
|
FINISHED |
| Object | potential impact on organizational operations |
—
|
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: potential impact on organizational operations | Statement: [FIPS 199, impactAssessmentCriterion, potential impact on organizational operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactAssessmentCriterion Context triple: [FIPS 199, impactAssessmentCriterion, potential impact on organizational operations]
-
A.
impactCategory
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
B.
measuresImpactIn
Indicates that an action or entity evaluates or quantifies its effect or influence within a specified context, domain, or environment.
-
C.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
D.
evaluationAspect
chosen
Indicates the specific dimension or criterion of performance or quality that is being assessed within an evaluation.
-
E.
impactStatus
Indicates the current state or condition of how something has affected or influenced a target.
- 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_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:01 p.m.