Triple
T3054357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Security Agency Exceptional Civilian Service Award |
E60443
|
entity |
| Predicate | scopeOfImpact |
P14568
|
FINISHED |
| Object | agency-wide |
—
|
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: agency-wide | Statement: [National Security Agency Exceptional Civilian Service Award, scopeOfImpact, agency-wide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scopeOfImpact Context triple: [National Security Agency Exceptional Civilian Service Award, scopeOfImpact, agency-wide]
-
A.
scopeOfContribution
Indicates the specific area, domain, or extent within which an entity’s contribution or involvement applies.
-
B.
scopeOfUse
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
-
C.
scopeType
Indicates the specific range, level, or context within which a given relationship, rule, or action is defined or applies.
-
D.
coverageScope
chosen
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
-
E.
majorImpact
Indicates that one entity has a significant, highly influential, or transformative effect on another entity or outcome.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf51b5081908ce355a76cfa9e3c |
completed | March 8, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.