Triple

T23097697
Position Surface form Disambiguated ID Type / Status
Subject Targovishte E575939 entity
Predicate historicalRegion P915 FINISHED
Object Ludogorie 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: Ludogorie | Statement: [Targovishte, historicalRegion, Ludogorie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ludogorie
Context triple: [Targovishte, historicalRegion, Ludogorie]
  • A. Ludogorie region chosen
    The Ludogorie region is a historical and geographical area in northeastern Bulgaria known for its rolling plateaus, mixed forests, and rich archaeological heritage.
  • B. Botevgrad
    Botevgrad is a town in western Bulgaria named in honor of the national revolutionary and poet Hristo Botev.
  • C. Reutov
    Reutov is a town in western Russia that functions as a suburban satellite of Moscow, known for its residential areas and proximity to the capital.
  • D. Sevlievo
    Sevlievo is a Bulgarian town known for its historical heritage, traditional crafts, and location near the Balkan Mountains in the Gabrovo Province.
  • E. Vizela
    Vizela is a Portuguese professional football club that competes in the country's top-tier league system.
  • 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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de61c7c8190809920fa1071935f completed April 29, 2026, 4:49 a.m.
Created at: April 17, 2026, 3:57 p.m.