Triple

T12399795
Position Surface form Disambiguated ID Type / Status
Subject Toro, Zamora, Spain E296219 entity
Predicate province P604 FINISHED
Object Zamora E239953 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: Zamora | Statement: [Toro, Zamora, Spain, province, Zamora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zamora
Context triple: [Toro, Zamora, Spain, province, Zamora]
  • A. Zamora
    Zamora is a city in the Mexican state of Michoacán known for its agricultural production, colonial architecture, and religious landmarks such as the Cathedral of Our Lady of Guadalupe.
  • B. Zamora
    Zamora is a city in southern Ecuador that serves as the administrative and commercial center of Zamora-Chinchipe Province in the Amazonian foothills.
  • C. Zamora chosen
    Zamora is a historic city in northwestern Spain known for its well-preserved Romanesque architecture and strategic location near the Portuguese border.
  • D. Navàs
    Navàs is a municipality in the comarca of Bages in the province of Barcelona, Catalonia, Spain.
  • E. Chichinales
    Chichinales is a small town in Argentina’s Patagonia region, located in the eastern part of Río Negro Province and known for its agricultural activity and proximity to the Alto Valle fruit-growing area.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9401cbfd481908ee6e765da3d12cb completed April 10, 2026, 6:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63efc0c7081909fe7d1818a081684 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:55 p.m.