Triple

T11276558
Position Surface form Disambiguated ID Type / Status
Subject Ivankovo Hydroelectric Station E266951 entity
Predicate locatedNear P294 FINISHED
Object Dubna E264944 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: Dubna | Statement: [Ivankovo Hydroelectric Station, locatedNear, Dubna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dubna
Context triple: [Ivankovo Hydroelectric Station, locatedNear, Dubna]
  • A. Dubna chosen
    Dubna is a Russian town in the Moscow Oblast best known as a major center for nuclear research and home to the Joint Institute for Nuclear Research.
  • B. Obninsk
    Obninsk is a Russian city best known as the site of the world’s first grid-connected nuclear power plant and an important center for nuclear and scientific research.
  • C. Dubna Urban Okrug
    Dubna Urban Okrug is a municipal formation in Moscow Oblast, Russia, that encompasses the science city of Dubna and its surrounding territory under a unified local government.
  • D. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • E. Kolpino
    Kolpino is a town in the Kolpinsky District of Saint Petersburg, Russia, known as an industrial suburb with significant metallurgical and manufacturing enterprises.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e966cb4c8190bc410d7e623e54db completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5258cc5208190be268ac6a82c9419 completed April 19, 2026, 6:57 p.m.
Created at: April 8, 2026, 9:31 p.m.