Triple

T17717321
Position Surface form Disambiguated ID Type / Status
Subject Mariánské Lázně E442232 entity
Predicate locatedIn P40 FINISHED
Object Cheb 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: Cheb District | Statement: [Mariánské Lázně, locatedIn, Cheb District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cheb District
Context triple: [Mariánské Lázně, 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. Marj District
    Marj District is an administrative district in northeastern Libya centered around the town of Marj.
  • 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_69d8b9ec79688190b86bdcef85a7b3aa completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47481663c8190a1110385e5596ab0 completed April 19, 2026, 6:21 a.m.
Created at: April 10, 2026, 10:06 a.m.