Triple
T35420694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FedRAMP security controls |
E1023779
|
entity |
| Predicate | targetData |
P96786
|
FINISHED |
| Object | federal information categorized as Low impact |
—
|
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: federal information categorized as Low impact | Statement: [FedRAMP security controls, targetData, federal information categorized as Low impact]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetData Context triple: [FedRAMP security controls, targetData, federal information categorized as Low impact]
-
A.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
B.
targetsVector
Indicates that one entity is directed toward, aimed at, or focused on another entity represented as a vector (e.g., a direction or target position).
-
C.
data
chosen
Indicates that one entity serves as informational content, measurements, or recorded values associated with another entity.
-
D.
targetsField
Indicates that one entity is directed toward, focuses on, or is intended to affect a specific field or attribute of another entity.
-
E.
targetPayload
Indicates that an action or system is directed toward or operates on a specific payload as its primary object or focus.
- 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_69f76df6704081909900c60be10d5849 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fed6da0390819096b88ef4714b144e |
completed | May 9, 2026, 6:40 a.m. |
| PD | Predicate disambiguation | batch_69fed53517d081909966f31707625f1a |
completed | May 9, 2026, 6:33 a.m. |
Created at: May 3, 2026, 4:03 p.m.