Triple

T17407886
Position Surface form Disambiguated ID Type / Status
Subject Pravets E423267 entity
Predicate locatedIn P40 FINISHED
Object Sofia Province 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: Sofia Province | Statement: [Pravets, locatedIn, Sofia Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sofia Province
Context triple: [Pravets, locatedIn, Sofia Province]
  • A. Sofia Province chosen
    Sofia Province is an administrative region in western Bulgaria that surrounds, but does not include, the national capital city of Sofia.
  • B. Sofia City Province
    Sofia City Province is the administrative region encompassing Bulgaria’s capital, Sofia, serving as the country’s political, economic, and cultural center.
  • C. Sofia Region
    Sofia Region is an administrative region in northern Madagascar known for its mountainous landscapes, including the country’s highest peak, Maromokotro.
  • D. Silistra Province
    Silistra Province is an administrative region in northeastern Bulgaria known for its Danube River border, agricultural economy, and historical city of Silistra.
  • E. Sliven Province
    Sliven Province is an administrative region in southeastern Bulgaria known for its mountainous landscapes, wine production, and the city of Sliven as its administrative center.
  • 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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43b08d5a881909e7a5b2ae2c60898 completed April 19, 2026, 2:16 a.m.
Created at: April 10, 2026, 5:46 a.m.