Triple

T16020827
Position Surface form Disambiguated ID Type / Status
Subject El Capricho E388591 entity
Predicate locatedIn P40 FINISHED
Object Comillas E886684 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: Comillas | Statement: [El Capricho, locatedIn, Comillas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Comillas
Context triple: [El Capricho, locatedIn, Comillas]
  • A. Comillas chosen
    Comillas is a coastal town in Cantabria, northern Spain, noted for its modernist architecture and historic buildings.
  • B. Tagüeña
    Tagüeña is a Spanish surname most notably associated with Manuel Tagüeña, a Republican military officer and physicist active during the Spanish Civil War.
  • C. Boca de Navíos
    Boca de Navíos is one of the straits in the Bocas del Dragón channel system that separates the island of Trinidad from the coast of Venezuela in the southeastern Caribbean.
  • D. Barra
    Barra is a scenic island in the Outer Hebrides of Scotland, known for its rugged coastline, Gaelic culture, and the unique beach runway at Barra Airport.
  • E. Barra
    Barra is an Arabic female given name historically borne by early Islamic-era women, including relatives of the Prophet Muhammad.
  • 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_69d86dabcb7c8190b6a39d6831d2fa1b completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183231f2c81908f4e4037c3aa180b completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf2c6128819091d8f3710578834e completed May 10, 2026, 12:19 a.m.
Created at: April 10, 2026, 4:55 a.m.