Triple
T1263938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euro |
E12559
|
entity |
| Predicate | replacedCurrency |
P2867
|
FINISHED |
| Object | Maltese lira |
E51444
|
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: Maltese lira | Statement: [Euro, replacedCurrency, Maltese lira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maltese lira Context triple: [Euro, replacedCurrency, Maltese lira]
-
A.
Maltese lira
chosen
The Maltese lira was the former national currency of Malta, used until it was replaced by the euro in 2008.
-
B.
Cypriot pound
The Cypriot pound was the former national currency of Cyprus, used until it was replaced by the euro in 2008.
-
C.
Tunisian dinar
The Tunisian dinar is the official monetary unit of Tunisia, subdivided into 1,000 millimes and used for all domestic financial transactions.
-
D.
Libyan dinar
The Libyan dinar is the official monetary unit of Libya, used for everyday transactions and economic activities throughout the country.
-
E.
Lebanese pound
The Lebanese pound is the official currency of Lebanon, historically pegged to the US dollar but heavily devalued in recent years due to the country’s financial crisis.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc8d6908190a5b2cf1051cc6d5e |
completed | March 1, 2026, 10:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2f1d1008190bd86948eb1b35b2d |
completed | March 7, 2026, 10:13 p.m. |
Created at: March 1, 2026, 7:50 p.m.