Triple

T18558151
Position Surface form Disambiguated ID Type / Status
Subject Diocese of San Sebastián E453558 entity
Predicate locatedIn P40 FINISHED
Object City of San Sebastián NE NERFINISHED

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: City of San Sebastián | Statement: [Diocese of San Sebastián, locatedIn, City of San Sebastián]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of San Sebastián
Context triple: [Diocese of San Sebastián, locatedIn, City of San Sebastián]
  • A. Donostia-San Sebastián chosen
    Donostia-San Sebastián is a coastal city in Spain’s Basque Country renowned for its picturesque bay, beaches, and world-class gastronomy.
  • B. Bilbao
    Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
  • C. Bilbao
    Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
  • D. San Sebastián
    San Sebastián is a small town located within the Comayagua Department of central Honduras.
  • E. San Sebastián
    San Sebastián is a Guatemalan town located in the highlands of the San Marcos department, known for its proximity to Central America’s highest peak, Volcán Tajumulco.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d388b0c881908e610a1c45b52640 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53808028c8190825630525d84a29b completed April 19, 2026, 8:16 p.m.
Created at: April 10, 2026, 11:41 a.m.