Triple

T44138
Position Surface form Disambiguated ID Type / Status
Subject Portugal E866 entity
Predicate capital P234 FINISHED
Object Lisbon E3151 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: Lisbon | Statement: [Portugal, capital, Lisbon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisbon
Context triple: [Portugal, capital, Lisbon]
  • A. Lisbon chosen
    Lisbon is the coastal capital city of Portugal, renowned for its historic architecture, hilly landscape, and role as a major cultural and economic center in Europe.
  • B. Albufeira
    Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
  • C. Madrid
    Madrid is the capital and largest city of Spain, renowned for its rich cultural heritage, historic architecture, and vibrant arts and nightlife scenes.
  • D. Rio de Janeiro
    Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
  • E. Portugal
    Portugal is a Southern European country on the Iberian Peninsula, known for its maritime history, Atlantic coastline, and role as one of the world’s earliest global colonial powers.
  • 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ae36824819080e8336a3c9f9bf8 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a26c17a9888190b8222d661165bd9f completed Feb. 28, 2026, 4:16 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.