Triple
T144019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NASA Distinguished Public Service Medal |
E2912
|
entity |
| Predicate | targetDomain |
P1902
|
FINISHED |
| Object | civil space program |
—
|
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: civil space program | Statement: [NASA Distinguished Public Service Medal, targetDomain, civil space program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetDomain Context triple: [NASA Distinguished Public Service Medal, targetDomain, civil space program]
-
A.
regulatoryDomain
Indicates that one entity defines or governs the rules, policies, or constraints under which another entity must operate.
-
B.
secondaryDomain
Indicates that one domain functions as a secondary or auxiliary domain in relation to a primary domain.
-
C.
usedInDomain
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
-
D.
primaryDomain
chosen
Indicates that one domain is the main or most important domain associated with an entity, as opposed to any secondary or alternate domains.
-
E.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257caf678819092e975d5167f9df4 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25656a4fc81908a87678ac3d28f93 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.