Triple

T12415686
Position Surface form Disambiguated ID Type / Status
Subject Cherven E296629 entity
Predicate locatedIn P40 FINISHED
Object Ruse Province E344499 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: Ruse Province | Statement: [Cherven, locatedIn, Ruse Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruse Province
Context triple: [Cherven, locatedIn, Ruse Province]
  • A. Ruse Province chosen
    Ruse Province is an administrative region in northern Bulgaria, centered on the Danube port city of Ruse and known for its role as a key transport and economic hub.
  • B. Silistra Province
    Silistra Province is an administrative region in northeastern Bulgaria known for its Danube River border, agricultural economy, and historical city of Silistra.
  • C. Varna Province
    Varna Province is an administrative region in northeastern Bulgaria centered around the Black Sea port city of Varna.
  • D. Shumen Province
    Shumen Province is an administrative region in northeastern Bulgaria known for its historical cities and archaeological sites, including the area around the early medieval capital Pliska.
  • E. Pleven Province
    Pleven Province is an administrative region in northern Bulgaria, known for its capital city Pleven and its location along the Danube River.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d6c4f6c8190bc99d3f7b64205c3 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b8077d081908e226e5bf856bcbf completed May 3, 2026, 12:49 a.m.
Created at: April 8, 2026, 9:55 p.m.