Triple

T70102
Position Surface form Disambiguated ID Type / Status
Subject Africa E1402 entity
Predicate hasColonialHistoryWith P3812 FINISHED
Object Portugal E866 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: Portugal | Statement: [Africa, hasColonialHistoryWith, Portugal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Portugal
Context triple: [Africa, hasColonialHistoryWith, Portugal]
  • A. Portugal chosen
    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.
  • B. Spain
    Spain is a southwestern European country on the Iberian Peninsula, historically a major global colonial power and now a constitutional monarchy and member of the European Union.
  • C. Algarve
    Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
  • D. Madeira
    Madeira is a Portuguese archipelago in the North Atlantic Ocean known for its rugged volcanic landscapes, mild subtropical climate, and namesake fortified wine.
  • E. Azores
    The Azores are a remote Portuguese archipelago in the North Atlantic Ocean, known for their volcanic landscapes, lush greenery, and mild maritime climate.
  • 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_69a24c06b3bc8190aa4ac89026115efc completed Feb. 28, 2026, 1:59 a.m.
NER Named-entity recognition batch_69a2567b592c8190aaf692a18fcd2f1b completed Feb. 28, 2026, 2:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2d0c0b92c819091c07cbbb7dda90a completed Feb. 28, 2026, 11:25 a.m.
Created at: Feb. 28, 2026, 2:03 a.m.