Triple

T2167211
Position Surface form Disambiguated ID Type / Status
Subject Don E46936 entity
Predicate tributary P415 FINISHED
Object Seversky Donets E93571 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: Seversky Donets | Statement: [Don, tributary, Seversky Donets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seversky Donets
Context triple: [Don, tributary, Seversky Donets]
  • A. Siverskyi Donets chosen
    Siverskyi Donets is a significant river in Eastern Europe that flows through Russia and eastern Ukraine, playing a key role in the region’s ecology, water supply, and ongoing geopolitical conflicts.
  • B. Kharkiv River
    The Kharkiv River is a waterway in northeastern Ukraine that flows through and lends its name to the city of Kharkiv before joining the Lopan River.
  • C. Vorskla River
    The Vorskla River is a significant tributary of the Dnieper River in central Ukraine, known for its historical battle sites and role in regional ecology and transport.
  • D. Dniester
    The Dniester is a major river in Eastern Europe that flows through Ukraine and Moldova before emptying into the Black Sea.
  • E. Dnieper
    The Dnieper is a major Eastern European river that flows through Russia, Belarus, and Ukraine before emptying into the Black Sea.
  • 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_69a88a184cbc8190877791f6552c2484 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbeac9d688190bfa68715e173771e completed March 7, 2026, 5:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6538c750819093d2e3f8e5f66a63 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:45 p.m.