Triple
T20830961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USDA Child Nutrition Programs |
E512823
|
entity |
| Predicate | healthGoal |
P102263
|
FINISHED |
| Object | reduce childhood hunger |
—
|
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: reduce childhood hunger | Statement: [USDA Child Nutrition Programs, healthGoal, reduce childhood hunger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthGoal Context triple: [USDA Child Nutrition Programs, healthGoal, reduce childhood hunger]
-
A.
hasHealthGoal
chosen
Indicates that an entity has a specific health-related objective or target it is aiming to achieve.
-
B.
goals
Indicates that an entity has objectives, targets, or desired outcomes it aims to achieve.
-
C.
goalType
Indicates the specific category or nature of a goal associated with an entity or action.
-
D.
legacyGoal
Indicates that an entity has a long-term, enduring objective or impact it aims to leave behind beyond its immediate actions or existence.
-
E.
goalIn
Indicates that one entity’s objective, aim, or intended outcome is located within, directed toward, or achieved inside another entity or 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_69e0b4cf62a88190bbf92351e9e57259 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c32177188190ad67572cb3b5db74 |
completed | April 21, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a1f4f48190aa9fb4ef8f8aea5a |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:42 p.m.