Triple

T23081296
Position Surface form Disambiguated ID Type / Status
Subject Kestenholz E575479 entity
Predicate district P2709 FINISHED
Object Gäu District 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: Gäu District | Statement: [Kestenholz, district, Gäu District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gäu District
Context triple: [Kestenholz, district, Gäu District]
  • A. Gäu District chosen
    Gäu District is an administrative district in the canton of Solothurn in northwestern Switzerland, known for its mix of industrial areas and agricultural landscapes along the Aare River.
  • B. Natá District
    Natá District is an administrative district in central Panama, located within Coclé Province and known for its historic colonial town of Natá de los Caballeros.
  • C. Bubi District
    Bubi District is an administrative district in Matabeleland North Province in western Zimbabwe, known largely for its rural communities and mining activities.
  • D. Baita District
    Baita District is an urban administrative district within the city of Liaoyang in Liaoning Province, northeastern China.
  • E. Hakui District
    Hakui District is a rural administrative district located in Ishikawa Prefecture on Japan’s Honshu island, known for its coastal landscapes and small towns.
  • 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_69e245be28d48190ad1348d5a73db37d completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18c67e06881908d24d6267bb49553 completed April 29, 2026, 4:43 a.m.
Created at: April 17, 2026, 3:56 p.m.