Triple
T4148151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monte Gordo |
E89837
|
entity |
| Predicate | currency |
P245
|
FINISHED |
| Object | Euro |
E12559
|
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: Euro | Statement: [Monte Gordo, currency, Euro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Euro Context triple: [Monte Gordo, currency, Euro]
-
A.
Euro
chosen
The Euro is the official common currency used by many countries in the European Union, facilitating trade and travel across much of Europe.
-
B.
Eurozone
The Eurozone is the group of European Union countries that have adopted the euro as their common official currency and share a unified monetary policy.
-
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
EURO is the commonly used short name for the UEFA European Championship, the premier international football tournament for national teams in Europe.
-
E.
European Quarter
The European Quarter is a district in Brussels that hosts many of the main institutions of the European Union, including parts of the European Parliament and European Commission.
- 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_69aed95a59a881909b26e70b42c6811a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02624a9c8190900e42e845ab7e4f |
completed | March 9, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f3136c48190b158142311bfbc6d |
completed | March 14, 2026, 3:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.