Triple
T25967996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | جيبوتي |
E645726
|
entity |
| Predicate | الديون_الرسمية |
P61067
|
FINISHED |
| Object | مرتفعة نسبياً مقارنة بحجم الاقتصاد |
—
|
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: مرتفعة نسبياً مقارنة بحجم الاقتصاد | Statement: [جيبوتي, الديون_الرسمية, مرتفعة نسبياً مقارنة بحجم الاقتصاد]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: الديون_الرسمية Context triple: [جيبوتي, الديون_الرسمية, مرتفعة نسبياً مقارنة بحجم الاقتصاد]
-
A.
debt
chosen
Indicates that one entity owes money or an obligation to another entity, typically to be repaid under agreed conditions.
-
B.
managedFederalDebt
Indicates that an entity is responsible for overseeing, controlling, or administering the federal government’s debt obligations.
-
C.
typeOfDebtManaged
Indicates the specific category or kind of debt that is being handled or overseen in the described relationship or context.
-
D.
debtorNationality
Indicates that the specified nationality is the country of citizenship or legal national affiliation of the debtor in the relationship.
-
E.
typicalDebtors
Indicates that one entity is typically or commonly a debtor to another entity, reflecting a usual debtor relationship between them.
- 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_69e77e8768648190b27bb578f14bcb88 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f604cc423081908edb1fcf694f06fc |
completed | May 2, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:50 a.m.