Triple
T668706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alessandro Volta 10000 lire banknote |
E12923
|
entity |
| Predicate | faceValueCurrency |
P2871
|
FINISHED |
| Object | ITL |
—
|
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: ITL | Statement: [Alessandro Volta 10000 lire banknote, faceValueCurrency, ITL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceValueCurrency Context triple: [Alessandro Volta 10000 lire banknote, faceValueCurrency, ITL]
-
A.
currency
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
-
B.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
C.
denominationType
Indicates the specific category or kind of denomination associated with an entity, such as its type within a broader classification of denominations.
-
D.
currencyAppearance
Indicates how a currency physically looks or is visually represented, such as its design, color, or format.
-
E.
banknoteDenomination
chosen
Indicates the specific face value assigned to a banknote in a given currency.
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49ff921288190a2e5edb201ba69ee |
completed | March 1, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69a49d18942c819083b3d1887e505900 |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.