Triple

T22992344
Position Surface form Disambiguated ID Type / Status
Subject Chara River E572084 entity
Predicate countrySubdivision P766 FINISHED
Object Irkutsk Oblast 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: Irkutsk Oblast | Statement: [Chara River, countrySubdivision, Irkutsk Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irkutsk Oblast
Context triple: [Chara River, countrySubdivision, Irkutsk Oblast]
  • A. Irkutsk Oblast chosen
    Irkutsk Oblast is a large federal subject of Russia in southeastern Siberia, known for its vast taiga landscapes, significant rivers, and proximity to Lake Baikal.
  • B. Omsk Oblast
    Omsk Oblast is a federal subject of southwestern Siberia in Russia, centered on the city of Omsk and known for its industrial base and agricultural production.
  • C. Tyumen Oblast
    Tyumen Oblast is a large federal subject in western Siberia, Russia, known for its vast oil and gas reserves and key role in the country’s energy industry.
  • D. Yakutsk region
    The Yakutsk region is a vast, sparsely populated area in northeastern Siberia, Russia, known for its extreme subarctic climate and rich natural resources.
  • E. Tomsk Oblast
    Tomsk Oblast is a large administrative region in southwestern Siberia, Russia, known for its vast taiga forests, significant natural resources, and diverse indigenous populations.
  • 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_69e245b535808190adef8a9df3c584db completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182f017a88190b02d0649a3af5d99 completed April 29, 2026, 4:02 a.m.
Created at: April 17, 2026, 3:50 p.m.