Triple

T15421298
Position Surface form Disambiguated ID Type / Status
Subject São João Railway Bridge E369385 entity
Predicate locatedIn P40 FINISHED
Object Porto E95974 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: Porto | Statement: [São João Railway Bridge, locatedIn, Porto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Porto
Context triple: [São João Railway Bridge, locatedIn, Porto]
  • A. Porto chosen
    Porto is Portugal’s second-largest city, renowned for its historic riverside district, rich maritime heritage, and production of port wine.
  • B. 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.
  • C. 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.
  • D. 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).
  • E. Braga
    Braga is a historic city in northern Portugal known for its rich religious heritage, baroque architecture, and status as a regional cultural and educational center.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ebe7b1081908e6b9e6e128a8d5d completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a7d02a08190a1e34e3a014acea9 completed May 9, 2026, 11:29 a.m.
Created at: April 10, 2026, 3:20 a.m.