Triple

T33988
Position Surface form Disambiguated ID Type / Status
Subject United Nations Economic Commission for Europe E676 entity
Predicate hasMember P10 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: [United Nations Economic Commission for Europe, hasMember, Portugal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Portugal
Context triple: [United Nations Economic Commission for Europe, hasMember, 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. Azores
    The Azores are a remote Portuguese archipelago in the North Atlantic Ocean, known for their volcanic landscapes, lush greenery, and mild maritime climate.
  • E. Lisbon
    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.
  • 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_69a2479dec388190967ba648663442c9 completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a2487952bc8190a94ce39c70799c70 completed Feb. 28, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69a29e420aa0819085d796612c24bcac completed Feb. 28, 2026, 7:50 a.m.
Created at: Feb. 28, 2026, 1:44 a.m.