Triple
T11777454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Drawing Rights |
E280054
|
entity |
| Predicate | accountingUse |
P86100
|
FINISHED |
| Object | IMF unit of account |
—
|
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: IMF unit of account | Statement: [Special Drawing Rights, accountingUse, IMF unit of account]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accountingUse Context triple: [Special Drawing Rights, accountingUse, IMF unit of account]
-
A.
usedForAccounting
chosen
Indicates that something is employed in performing, supporting, or managing accounting activities or financial record-keeping.
-
B.
accrualMethod
Indicates the method or basis by which something (such as interest, revenue, or benefits) is accumulated or recognized over time.
-
C.
usedAccountingFirm
Indicates that one entity engaged the professional services of a particular accounting firm.
-
D.
usedInFinancialDocuments
Indicates that something is employed or appears within financial documents or records.
-
E.
revenueUse
Indicates how generated revenue is allocated, spent, or applied toward specific purposes or activities.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a8c2e8b08190a31b1e284fca2aee |
completed | April 10, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69d8a242cd8c819086ed6c5f292dc8cb |
completed | April 10, 2026, 7:09 a.m. |
Created at: April 8, 2026, 9:42 p.m.