Triple

T15879601
Position Surface form Disambiguated ID Type / Status
Subject Maly Zelenchuk River E385040 entity
Predicate mouth P407 FINISHED
Object Kuban River E57489 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: Kuban River | Statement: [Maly Zelenchuk River, mouth, Kuban River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuban River
Context triple: [Maly Zelenchuk River, mouth, Kuban River]
  • A. Kuban River chosen
    The Kuban River is a major river in the North Caucasus region of Russia that flows through the Krasnodar Krai before emptying into the Sea of Azov.
  • B. Kazan River
    The Kazan River is a major river in the Republic of Tatarstan, Russia, flowing through the city of Kazan before emptying into the Volga River.
  • C. Kuban
    Kuban is a Turkish surname most notably borne by the prominent architectural historian and scholar Doğan Kuban.
  • D. Voronezh River
    The Voronezh River is a major river in western Russia that flows through the city of Voronezh before joining the Don River.
  • E. Bobr River
    The Bobr River is a tributary watercourse in Belarus that flows through the central part of the country before joining the Berezina 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15600863c8190a2dbfd6d7ff495d7 completed April 16, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139e380bc81908452f6e8666f23ad completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 4:51 a.m.