Triple

T9843150
Position Surface form Disambiguated ID Type / Status
Subject Joint Institute for Nuclear Research E239274 entity
Predicate headquartersLocation P62 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: [Joint Institute for Nuclear Research, headquartersLocation, Dubna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dubna
Context triple: [Joint Institute for Nuclear Research, headquartersLocation, 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. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • D. Kolpino
    Kolpino is a town in the Kolpinsky District of Saint Petersburg, Russia, known as an industrial suburb with significant metallurgical and manufacturing enterprises.
  • E. Zvenigorod
    Zvenigorod is a historic town near Moscow, Russia, known for its ancient monasteries, traditional Russian architecture, and role as a cultural and spiritual center.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb35c8e348190aa090c71bf6f30eb completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1ead49b14819086a9bbd256f298a9 completed April 5, 2026, 4:53 a.m.
Created at: March 30, 2026, 8:33 p.m.