Triple
T1404778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungarian forint |
E31665
|
entity |
| Predicate | pluralForm |
P5088
|
FINISHED |
| Object | forint |
E162310
|
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: forint | Statement: [Hungarian forint, pluralForm, forint]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: forint Context triple: [Hungarian forint, pluralForm, forint]
-
A.
forint
chosen
The forint is the official currency of Hungary, used for everyday transactions and monetary policy in the country.
-
B.
inti
Inti was the former official currency of Peru, used during the late 20th century before being replaced due to hyperinflation.
-
C.
FRO
FRO is the three-letter ISO 3166-1 alpha-3 country code assigned to the Faroe Islands.
-
D.
FIO
FIO is the acronym for the Federal Insurance Office, a U.S. Treasury Department agency that monitors the insurance industry and advises on national and international insurance policy.
-
E.
FÜ
FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad015839908190b7f9f6c79dcc0367 |
completed | March 8, 2026, 4:55 a.m. |
Created at: March 1, 2026, 7:59 p.m.