Triple

T1770358
Position Surface form Disambiguated ID Type / Status
Subject Östersund E38859 entity
Predicate hasTwinningRelationshipWith P919 FINISHED
Object Yekaterinburg E38566 NE FINISHED

How this triple was built (3 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: Yekaterinburg | Statement: [Östersund, hasTwinningRelationshipWith, Yekaterinburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yekaterinburg
Context triple: [Östersund, hasTwinningRelationshipWith, Yekaterinburg]
  • A. Yekaterinburg chosen
    Yekaterinburg is a major industrial and cultural city in Russia’s Ural region, historically known as the site of the execution of the last Russian tsar, Nicholas II, and his family.
  • B. Omsk
    Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
  • C. Novosibirsk
    Novosibirsk is a major city in southwestern Siberia and the third-largest city in Russia, known as an important industrial, scientific, and cultural center.
  • D. Nizhny Tagil
    Nizhny Tagil is a major industrial city in Russia’s Sverdlovsk Oblast, historically known for its metallurgical plants and role in the country’s heavy industry.
  • E. Krasnoyarsk
    Krasnoyarsk is a large industrial and cultural city in central Russia, situated on the Yenisei River and known as one of the key urban centers of Siberia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTwinningRelationshipWith
Context triple: [Östersund, hasTwinningRelationshipWith, Yekaterinburg]
  • A. hasTwin
    Indicates that one entity is a twin of another, sharing the same birth event or time with a sibling.
  • B. hasTwinChildren
    Indicates that an entity is the parent of children who are twins.
  • C. hasTwinTown chosen
    Indicates that two towns or cities are officially paired in a twinning relationship, typically for cultural, social, or economic exchange.
  • D. hasTwinActors
    Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within a given context.
  • E. hasFamilialTieTo
    Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
  • F. None of above.

Provenance (4 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_69a8862e61708190af97b9838cc3f5de completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69ab39fc2c448190bfaf1ee8d474632a completed March 6, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d7d1f6c8190a1033c784091ffb8 completed March 9, 2026, 5:41 a.m.
PD Predicate disambiguation batch_69aa61cbb1288190a7ba38b61905f578 completed March 6, 2026, 5:10 a.m.
Created at: March 4, 2026, 7:31 p.m.