Triple
T31309807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebanese financial crisis |
E798430
|
entity |
| Predicate | currencyAffected |
P245
|
FINISHED |
| Object | Lebanese pound |
—
|
NE NERFINISHED |
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: Lebanese pound | Statement: [Lebanese financial crisis, currencyAffected, Lebanese pound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currencyAffected Context triple: [Lebanese financial crisis, currencyAffected, Lebanese pound]
-
A.
currencyOnOtherSide
Indicates that one currency is located or used on the opposite side of a specified reference point, boundary, or transaction relative to another currency.
-
B.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
C.
currencyDepicted
Indicates that one entity visually represents or shows the image or symbol of a particular currency on it.
-
D.
currency
chosen
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
-
E.
currencyGiven
Indicates that one entity transfers or provides money or a monetary unit to another entity.
- 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_69f224e1932c81908fef14f7b03a10b7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe163a41a0819098403b470e327d29 |
completed | May 8, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69fe1358db5c819092570814a37ef5bd |
completed | May 8, 2026, 4:46 p.m. |
Created at: April 29, 2026, 9:15 p.m.