Triple

T22563711
Position Surface form Disambiguated ID Type / Status
Subject Art Gallery Stanislav Dospevski E557885 entity
Predicate location P40 FINISHED
Object Pazardzhik, Bulgaria 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: Pazardzhik, Bulgaria | Statement: [Art Gallery Stanislav Dospevski, location, Pazardzhik, Bulgaria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pazardzhik, Bulgaria
Context triple: [Art Gallery Stanislav Dospevski, location, Pazardzhik, Bulgaria]
  • A. Pazardzhik, Bulgaria
    Pazardzhik is a city in southern Bulgaria known as a regional administrative and cultural center on the banks of the Maritsa River.
  • B. Pazardzhik chosen
    Pazardzhik is a city in southern Bulgaria known as a regional economic and cultural center in the Upper Thracian Plain.
  • C. Dimitrovgrad, Bulgaria
    Dimitrovgrad, Bulgaria is an industrial town in southern Bulgaria known for its planned socialist-era architecture and location near the Maritsa River.
  • D. Sapareva Banya
    Sapareva Banya is a Bulgarian spa town renowned for its hot mineral springs and the hottest geyser in continental Europe.
  • E. Pravets, Bulgaria
    Pravets, Bulgaria is a small town in western Bulgaria known as the birthplace of longtime communist leader Todor Zhivkov and for its role in the country’s electronics industry.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15fa7a828819096804ac928e2aaf9 completed April 29, 2026, 1:32 a.m.
Created at: April 16, 2026, 8:52 p.m.