Triple

T17154669
Position Surface form Disambiguated ID Type / Status
Subject euro E416311 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. Corsican lira
    The Corsican lira was the short-lived monetary unit used in 18th-century Corsica during its brief period of independence under the Corsican Republic.
  • D. Tunisian dinar
    The Tunisian dinar is the official monetary unit of Tunisia, subdivided into 1,000 millimes and used for all domestic financial transactions.
  • E. Libyan dinar
    The Libyan dinar is the official monetary unit of Libya, used for everyday transactions and economic activities throughout the country.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f40a6b7c8190838e588c4fd81d95 completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01415f3cd481908e96ca294cf3b247 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:37 a.m.