Triple

T15539093
Position Surface form Disambiguated ID Type / Status
Subject E370428 entity
Predicate locatedIn P40 FINISHED
Object Cheb District E442231 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: Cheb District | Statement: [Aš, locatedIn, Cheb District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheb District
Context triple: [Aš, locatedIn, Cheb District]
  • A. Cheb District chosen
    Cheb District is an administrative district in the western Czech Republic, bordering Germany and known for its historic town of Cheb and surrounding spa and natural areas.
  • B. Masin District
    Masin District is an administrative district located within Huari Province in the Ancash Region of Peru, known for its Andean highland geography and rural communities.
  • C. Nazyan District
    Nazyan District is an administrative district in eastern Afghanistan known for its predominantly Pashtun population and location within Nangarhar Province near the Pakistan border.
  • D. Qatana District
    Qatana District is an administrative district in southern Syria, located within the Rif Dimashq Governorate surrounding the capital, Damascus.
  • E. Siha District
    Siha District is an administrative district in northern Tanzania, located within the Kilimanjaro Region near the slopes of Mount Kilimanjaro.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04430b5188190a555a3cd4fb0c61c completed April 16, 2026, 2:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d626e688190bd93481cfd6cb255 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 4:07 a.m.