Triple
T117893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Agency for International Development |
E2381
|
entity |
| Predicate | typeOfAidProvided |
P936
|
FINISHED |
| Object | bilateral development assistance |
—
|
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: bilateral development assistance | Statement: [United States Agency for International Development, typeOfAidProvided, bilateral development assistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfAidProvided Context triple: [United States Agency for International Development, typeOfAidProvided, bilateral development assistance]
-
A.
typeOfSupport
chosen
Indicates the kind or category of assistance, help, or backing provided in a given context.
-
B.
reconstructedWithAidProgram
Indicates that an entity was rebuilt or restored through the support or resources provided by an aid program.
-
C.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
D.
donated
Indicates that one entity voluntarily gave something of value (such as money, goods, or time) to another entity, typically without expecting anything in return.
-
E.
exemptionType
Indicates the specific category or kind of exemption that applies in 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a257845c548190bfb49409988d1c57 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a256456d908190b52c937fe6c4343f |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.