Triple
T11148083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egypt–United States relations |
E263717
|
entity |
| Predicate | annualUSEconomicAidApprox |
P432
|
FINISHED |
| Object | hundreds of millions of USD |
—
|
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: hundreds of millions of USD | Statement: [Egypt–United States relations, annualUSEconomicAidApprox, hundreds of millions of USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: annualUSEconomicAidApprox Context triple: [Egypt–United States relations, annualUSEconomicAidApprox, hundreds of millions of USD]
-
A.
receivesMilitaryAidFrom
Indicates that one entity obtains military assistance, such as equipment, training, or funding, from another entity.
-
B.
providedMilitaryAidTo
Indicates that one entity has supplied military assistance, such as weapons, training, funding, or logistical support, to another entity.
-
C.
purchasedByUnitedStatesIn
Indicates that something was bought or acquired by the United States during a specified time period.
-
D.
totalAidAmountUSD
chosen
Indicates the total monetary value of aid provided, expressed in U.S. dollars.
-
E.
WorldBankMember
Indicates that an entity is a member country or organization formally belonging to the World Bank.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8701ea481908c86c2359f5dc957 |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.