Triple

T7480998
Position Surface form Disambiguated ID Type / Status
Subject Red Line (Lisbon Metro) E176756 entity
Predicate cityServed P82 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: [Red Line (Lisbon Metro), cityServed, Lisbon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisbon
Context triple: [Red Line (Lisbon Metro), cityServed, 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. Coimbra
    Coimbra is a historic Portuguese city known for its medieval architecture and the University of Coimbra, one of the oldest universities in continuous operation in the world.
  • 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_69c69f236ce08190a04d7679f03b29b2 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f534aa388190b3bb3e16be3a54c8 completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c845fd62dc8190a64f5464a204c0d2 completed March 28, 2026, 9:19 p.m.
Created at: March 27, 2026, 3:42 p.m.