Triple

T2299287
Position Surface form Disambiguated ID Type / Status
Subject Ural region E51691 entity
Predicate majorCity P316 FINISHED
Object Tyumen E232706 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: Tyumen | Statement: [Ural region, majorCity, Tyumen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyumen
Context triple: [Ural region, majorCity, Tyumen]
  • A. Tyumen chosen
    Tyumen is a historic city in western Siberia, Russia, known as an early Russian settlement in Siberia and now a major industrial and administrative center.
  • B. 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.
  • C. Irkutsk
    Irkutsk is a major city in southeastern Siberia, Russia, historically significant as a political and administrative center and a key hub during the Russian Civil War.
  • D. Yakutsk
    Yakutsk is a major city in northeastern Siberia, Russia, known as one of the coldest large cities in the world and a key administrative and cultural center of the Sakha Republic.
  • E. 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.
  • 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5ec3c948190b47ea763812a1cf5 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69b12ded5f9c8190a0de21b631d970b0 completed March 11, 2026, 8:55 a.m.
Created at: March 4, 2026, 7:49 p.m.