Triple

T12354385
Position Surface form Disambiguated ID Type / Status
Subject Pernik E294570 entity
Predicate isPartOf P10 FINISHED
Object Pernik Province E294567 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: Pernik Province | Statement: [Pernik, isPartOf, Pernik Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pernik Province
Context triple: [Pernik, isPartOf, Pernik Province]
  • A. Pernik Province chosen
    Pernik Province is a region in western Bulgaria known for its industrial heritage and proximity to the capital, Sofia.
  • B. Tak province
    Tak province is a mountainous and forested region in western Thailand, known for its border with Myanmar, scenic national parks, and the gateway town of Mae Sot.
  • C. Oruzgan Province
    Oruzgan Province is a central Afghan province known for its mountainous terrain, tribal Pashtun population, and strategic role in Afghanistan’s recent conflicts.
  • D. Berar Province
    Berar Province was a former administrative region in central India under British rule, known for its cotton-growing areas and later incorporation into the Central Provinces and Berar.
  • E. Skikda Province
    Skikda Province is a coastal region in northeastern Algeria known for its Mediterranean port city of Skikda and its role in the country’s modern history.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f8bc60c8190b0ceb84093e70db4 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ab2dc30819082b12fa35f585762 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:54 p.m.