Triple
T4502474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | casino at Royale-les-Eaux |
E101252
|
entity |
| Predicate | currencyUsedInGambling |
P188
|
FINISHED |
| Object | French francs |
—
|
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: French francs | Statement: [casino at Royale-les-Eaux, currencyUsedInGambling, French francs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currencyUsedInGambling Context triple: [casino at Royale-les-Eaux, currencyUsedInGambling, French francs]
-
A.
typeOfGambling
Indicates the specific category or form of gambling activity associated with an entity.
-
B.
currencyType
Indicates the specific kind of monetary unit or currency associated with an entity or transaction.
-
C.
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).
-
D.
usesCurrency
chosen
Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
-
E.
currencyDepicted
Indicates that one entity visually represents or shows the image or symbol of a particular currency on it.
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56fb2bec8190b74b6a49d9475514 |
completed | March 20, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69bd521671688190bc655d25fa77eba2 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1 p.m.