Triple
T20802306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | School Breakfast Program |
E512069
|
entity |
| Predicate | reimburses |
P66766
|
FINISHED |
| Object | schools for eligible breakfasts served |
—
|
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: schools for eligible breakfasts served | Statement: [School Breakfast Program, reimburses, schools for eligible breakfasts served]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reimburses Context triple: [School Breakfast Program, reimburses, schools for eligible breakfasts served]
-
A.
reimbursableDefinition
Indicates that one entity defines the rules, conditions, or criteria under which another entity is eligible to be reimbursed.
-
B.
disburses
chosen
Indicates the act of paying out or distributing funds or resources from a source to a recipient.
-
C.
refundable
Indicates that an item, service, or payment can be returned or canceled in exchange for a reimbursement of money.
-
D.
reimbursementCategory
Indicates the classification or type under which a reimbursement claim or expense is categorized.
-
E.
payReform
Indicates a relationship where an authority changes or restructures the pay system, such as salaries or compensation terms, for a group of people.
- 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_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2b207c48190a9ca5895bdf85245 |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:39 p.m.