Triple

T4194896
Position Surface form Disambiguated ID Type / Status
Subject Sura River E89123 entity
Predicate flowsThrough P225 FINISHED
Object Penza Oblast E577191 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: Penza Oblast | Statement: [Sura River, flowsThrough, Penza Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Penza Oblast
Context triple: [Sura River, flowsThrough, Penza Oblast]
  • A. Penza Oblast chosen
    Penza Oblast is a federal subject of central Russia known for its agricultural economy, mixed forests, and role as a regional industrial and cultural center.
  • B. Kostroma Oblast
    Kostroma Oblast is a federal subject in central Russia known for its historic towns and forests, situated along the middle reaches of the Volga River.
  • C. Ryazan Oblast
    Ryazan Oblast is a federal subject of central Russia known for its historic cities, agricultural landscapes, and location along the Oka River southeast of Moscow.
  • D. Lipetsk Oblast
    Lipetsk Oblast is a federal subject of western Russia known for its industrial centers, agricultural production, and administrative capital, the city of Lipetsk.
  • E. Kaluga Oblast
    Kaluga Oblast is a federal subject of western Russia known for its historical cities, space industry heritage, and location southwest of Moscow.
  • 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_69aed9569a4481908b6c1fcec2a11e21 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af034406348190a56c21b5c08a6828 completed March 9, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce1c351f848190a1f91a09f7319a01 completed April 2, 2026, 7:35 a.m.
Created at: March 9, 2026, 3:46 p.m.