Triple
T22399084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lavia |
E553710
|
entity |
| Predicate | currencyCode |
P208
|
FINISHED |
| Object | EUR |
—
|
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: EUR | Statement: [Lavia, currencyCode, EUR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EUR Context triple: [Lavia, currencyCode, EUR]
-
A.
EUR
EUR is the commonly used abbreviation for the Bureau of European and Eurasian Affairs within the U.S. Department of State, which oversees American foreign policy and diplomatic relations in Europe and Eurasia.
-
B.
EURO
EURO is the commonly used short name for the UEFA European Championship, the premier international football tournament for national teams in Europe.
-
C.
EURO
EURO is the commonly used abbreviation for the World Health Organization’s Regional Office for Europe, which oversees public health initiatives across the European region.
-
D.
euro
chosen
The euro is the official common currency used by most countries in the European Union and one of the world's major reserve and trading currencies.
-
E.
€STR
€STR is the euro short-term rate, a key overnight benchmark interest rate for the euro area used in financial markets and contracts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b28e58819090624f131ce63a9f |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 16, 2026, 8:46 p.m.