Triple

T18920479
Position Surface form Disambiguated ID Type / Status
Subject Metropolis of Serres and Nigrita E462838 entity
Predicate hasTerritory P285 FINISHED
Object Serres region NE NERFINISHED

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: Serres region | Statement: [Metropolis of Serres and Nigrita, hasTerritory, Serres region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serres region
Context triple: [Metropolis of Serres and Nigrita, hasTerritory, Serres region]
  • A. Serres
    Serres is a French surname most notably associated with the philosopher and historian of science Michel Serres.
  • B. Serres chosen
    Serres is a historic city in northern Greece known for its Byzantine heritage and role as a regional economic and cultural center.
  • C. Monchique region
    The Monchique region is a mountainous area in Portugal’s Algarve known for its lush landscapes, thermal springs, and traditional rural villages.
  • D. Zamora Province
    Zamora Province is a largely rural administrative region in northwestern Spain, known for its historic capital city of Zamora, Romanesque architecture, and location near the Portuguese border.
  • E. La Vera region
    La Vera region is a picturesque comarca in northern Cáceres, Extremadura, Spain, known for its lush landscapes, gorges, paprika production, and historic villages.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c62a264c81909f6d5df841486efc completed April 20, 2026, 6:22 a.m.
Created at: April 10, 2026, 11:59 a.m.