Triple

T4960058
Position Surface form Disambiguated ID Type / Status
Subject Tagus River estuary E111382 entity
Predicate adjacentTo P224 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: [Tagus River estuary, adjacentTo, Lisbon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisbon
Context triple: [Tagus River estuary, adjacentTo, 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_69bd4419393c819086319a6fe4bf8542 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71da80008190a0d606d5091822b8 completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81a9d8f08190ac79ca210356aab4 completed March 21, 2026, 11:31 a.m.
Created at: March 20, 2026, 1:32 p.m.