Triple

T3727363
Position Surface form Disambiguated ID Type / Status
Subject Rentería E81781 entity
Predicate near P350 FINISHED
Object San Sebastián E138087 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: San Sebastián | Statement: [Rentería, near, San Sebastián]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Sebastián
Context triple: [Rentería, near, San Sebastián]
  • A. 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.
  • B. 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.
  • C. 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.
  • D. Pamplona
    Pamplona is a historic city in northern Spain, best known internationally for its annual Running of the Bulls during the San Fermín festival.
  • E. Pamplona
    Pamplona is a landlocked agricultural municipality in the province of Negros Oriental in the Philippines, known for its hilly terrain and rural communities.
  • 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_69ad8b1b7ef081908d2d381bbf54985a completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcaf7a6908190bd0c3bb5c55ab9ee completed March 8, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db1102a08190b5965c474dfab6db completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:34 p.m.