Triple
T12528086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Employment and Training Administration |
E299489
|
entity |
| Predicate | typeOfProgramPortfolio |
P2192
|
FINISHED |
| Object | discretionary grants |
—
|
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: discretionary grants | Statement: [Employment and Training Administration, typeOfProgramPortfolio, discretionary grants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfProgramPortfolio Context triple: [Employment and Training Administration, typeOfProgramPortfolio, discretionary grants]
-
A.
typicalPortfolio
Indicates that one entity is the standard or representative portfolio associated with another entity (such as a person, account, or organization).
-
B.
portfolioOf
Indicates that one entity is the collection of investments, works, or assets that are owned, managed, or represented by another entity.
-
C.
typeOfProject
Indicates the specific category or kind of project that an entity is associated with or classified under.
-
D.
programType
chosen
Indicates the category or kind of program to which an entity belongs or with which it is associated.
-
E.
eligibleProjectType
Indicates that a project belongs to a category or type that qualifies it for a specific program, process, or benefit.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.