Triple
T10247687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CFA franc |
E240259
|
entity |
| Predicate | hasISO4217Code |
P189
|
FINISHED |
| Object | XOF |
E122066
|
NE 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: XOF | Statement: [CFA franc, hasISO4217Code, XOF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XOF Context triple: [CFA franc, hasISO4217Code, XOF]
-
A.
XOF
chosen
XOF is the West African CFA franc, a regional currency used by several West African countries including Niger.
-
B.
XSF
XSF is the nonprofit organization that develops and maintains the open XMPP communication protocols used for instant messaging and real-time communication.
-
C.
OFB
OFB is an Indian government organization that historically managed a network of ordnance factories responsible for producing arms, ammunition, and military equipment for the country's armed forces.
-
D.
Cif
Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
-
E.
XAF
XAF is the currency code for the Central African CFA franc, a regional currency used by several Central African countries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d22e0d4c8190a6712859924e9d3d |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7ade8448190830d950b7cee0c34 |
completed | April 9, 2026, 12:49 a.m. |
Created at: April 6, 2026, 11:27 a.m.