Triple
T27460108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring |
E692711
|
entity |
| Predicate | levelOfImpact |
P97046
|
FINISHED |
| Object | national |
—
|
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: national | Statement: [Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring, levelOfImpact, national]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: levelOfImpact Context triple: [Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring, levelOfImpact, national]
-
A.
impactLevel
Indicates the degree or intensity of effect that one entity, action, or event has on another.
-
B.
affectedLevel
Indicates the degree or extent to which one entity is impacted or influenced by another entity or event.
-
C.
hasImpactScale
chosen
Indicates the degree or magnitude of impact that one entity or action has on another, typically expressed along a defined scale.
-
D.
impactDescription
Indicates a description of the effect, consequence, or influence that one entity, action, or event has on another.
-
E.
typicalLevelOfInfluence
Indicates the usual degree or strength of influence one entity exerts over another or within a given context.
- 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_69ef5207903881909427745cda05d27a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62df94be88190bcb43f8106c762dd |
completed | May 2, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 12:49 p.m.