Triple

T14368270
Position Surface form Disambiguated ID Type / Status
Subject Afonso Costa E356289 entity
Predicate residence P75 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: [Afonso Costa, residence, Lisbon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisbon
Context triple: [Afonso Costa, residence, 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. Lisbon
    Lisbon is the alias of Raquel Murillo, a former police inspector who becomes one of the central members of the Professor’s gang in the Spanish series "Money Heist" (La Casa de Papel).
  • C. Porto
    Porto is Portugal’s second-largest city, renowned for its historic riverside district, rich maritime heritage, and production of port wine.
  • D. Porto
    Porto is a small coastal town in western Corsica, France, known as the main gateway to the scenic Gulf of Porto and its surrounding natural reserves and rock formations.
  • E. City of Lisbon
    The City of Lisbon is the municipal government authority responsible for administering and providing local services to the community of Lisbon, Iowa.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8faf00e8819087d7100e9d8c1877 completed April 14, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d7c397c81908dab10dd8d7aa367 completed May 8, 2026, 4:58 a.m.
Created at: April 10, 2026, 1:15 a.m.