Triple

T4488377
Position Surface form Disambiguated ID Type / Status
Subject Darmstadt E107304 entity
Predicate twinCity P1072 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: [Darmstadt, twinCity, San Sebastián]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Sebastián
Context triple: [Darmstadt, twinCity, 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52ad36748190b791de458f2116b2 completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd67a31d0c819089954c8af4b1bdd6 completed March 20, 2026, 3:28 p.m.
Created at: March 20, 2026, 12:59 p.m.