Triple

T17966384
Position Surface form Disambiguated ID Type / Status
Subject Bryansk Oblast E449218 entity
Predicate containsCity P294 FINISHED
Object Klintsy E1099025 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: Klintsy | Statement: [Bryansk Oblast, containsCity, Klintsy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Klintsy
Context triple: [Bryansk Oblast, containsCity, Klintsy]
  • A. Klintsy chosen
    Klintsy is a city in western Russia known as an industrial and cultural center within Bryansk Oblast.
  • B. Krasny Kut
    Krasny Kut is a small town in southwestern Russia known as an administrative and agricultural center within the Saratov region.
  • C. Monastyryshche
    Monastyryshche is a small town in central Ukraine that serves as a local administrative and cultural center within Cherkasy Oblast.
  • D. Bronnitsy
    Bronnitsy is a historic town in Russia known for its jewelry-making traditions and its location southeast of Moscow along the Moskva River.
  • E. Kostopil
    Kostopil is a town in western Ukraine known for its industrial activity and location within the historical region of Volhynia.
  • 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b1380960819089a3c0dd7cd57e5e completed April 19, 2026, 10:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a037c25fae48190b9ea3dca4539a9a0 completed May 12, 2026, 7:14 p.m.
Created at: April 10, 2026, 10:22 a.m.