Triple

T4289185
Position Surface form Disambiguated ID Type / Status
Subject Getaria E97344 entity
Predicate locatedNear P294 FINISHED
Object Zarautz E262586 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: Zarautz | Statement: [Getaria, locatedNear, Zarautz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zarautz
Context triple: [Getaria, locatedNear, Zarautz]
  • A. Zarautz chosen
    Zarautz is a coastal town in Spain’s Basque Country, known for its long sandy beach and strong surfing culture.
  • B. Errenteria
    Errenteria is a town and municipality in the province of Gipuzkoa in Spain’s Basque Country, known for its industrial heritage and proximity to San Sebastián.
  • 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. Arzachena
    Arzachena is a town in northeastern Sardinia, Italy, known for its archaeological sites and proximity to the Costa Smeralda resort area.
  • E. Orduña
    Orduña is a historic town in the Basque Country of northern Spain, known for its medieval heritage and strategic location along traditional trade routes.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35060b70081908479c95b2afe8ec5 completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7307e3481909dfb55018f359589 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.