Triple

T889848
Position Surface form Disambiguated ID Type / Status
Subject Sakha Republic E19214 entity
Predicate river P165 FINISHED
Object Lena River E17170 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: Lena River | Statement: [Sakha Republic, river, Lena River]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lena River
Context triple: [Sakha Republic, river, Lena River]
  • A. Lena River chosen
    The Lena River is one of the longest rivers in the world, flowing through Siberia in northeastern Russia to the Arctic Ocean.
  • B. Ural River
    The Ural River is a major river in Russia and Kazakhstan that traditionally marks part of the boundary between the European and Asian continents.
  • C. Okhta River
    The Okhta River is a tributary waterway in northwestern Russia that flows through Saint Petersburg before joining the Neva River.
  • D. Yenisei River
    The Yenisei River is one of the longest rivers in Asia, flowing northward through Siberia to the Arctic Ocean and forming a major part of the central Eurasian river system.
  • E. Samara River
    The Samara River is a significant river in European Russia that flows through the Samara region before joining the Volga 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad0086a081908c47c285896a1f3c completed March 1, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac99669a1481909fa42162ffee2d7b completed March 7, 2026, 9:32 p.m.
Created at: March 1, 2026, 7:39 p.m.