Triple

T176669
Position Surface form Disambiguated ID Type / Status
Subject Italian language E3588 entity
Predicate spokenIn P2266 FINISHED
Object Malta E9342 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: Malta | Statement: [Italian language, spokenIn, Malta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malta
Context triple: [Italian language, spokenIn, Malta]
  • A. Malta chosen
    Malta is a small island nation in the central Mediterranean known for its rich history, strategic location, and membership in the European Union.
  • B. San Marino
    San Marino is a small, landlocked microstate surrounded by Italy, known as one of the world’s oldest republics and a popular tourist destination.
  • C. Cyprus
    Cyprus is an island country in the Eastern Mediterranean known for its strategic location, divided capital Nicosia, and blend of Greek and Turkish cultural influences.
  • D. Corsica
    Corsica is a mountainous Mediterranean island and French territorial collectivity known for its distinct culture, rugged coastline, and as the birthplace of Napoleon Bonaparte.
  • E. Albania
    Albania is a Balkan country in Southeastern Europe known for its mountainous landscapes, Adriatic and Ionian coastlines, and a history shaped by Ottoman rule, communism, and post–Cold War transition.
  • 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_69a25374990081909766d30c79a18e0e completed Feb. 28, 2026, 2:31 a.m.
NER Named-entity recognition batch_69a258fd278481908ad4498e03f38e2f completed Feb. 28, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a35b61bdfc8190a399f0b4f09672ab completed Feb. 28, 2026, 9:17 p.m.
Created at: Feb. 28, 2026, 2:39 a.m.