Triple
T31307782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States to Latin America remittance corridor |
E798379
|
entity |
| Predicate | mainUseOfFunds |
P171559
|
FINISHED |
| Object | household consumption |
—
|
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: household consumption | Statement: [United States to Latin America remittance corridor, mainUseOfFunds, household consumption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainUseOfFunds Context triple: [United States to Latin America remittance corridor, mainUseOfFunds, household consumption]
-
A.
usedFund
Indicates that one entity expended or applied a particular fund or financial resource for some purpose.
-
B.
excludedUseOfFundsFor
Indicates that certain funds are prohibited from being used for a specified purpose or activity.
-
C.
usedFundingFrom
Indicates that one entity utilized financial resources that originated from another entity.
-
D.
capitalUse
Indicates the use or application of financial capital by one entity in relation to another entity or activity.
-
E.
fundingFocus
Indicates that one entity’s funding is directed toward or prioritized for a particular target, theme, or area of activity.
- F. None of above. chosen
Provenance (4 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_69f224e0bd4c8190aab9b29a73f7aa3c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 29, 2026, 9:14 p.m.