Triple

T21330750
Position Surface form Disambiguated ID Type / Status
Subject European route E22 E525890 entity
Predicate passesThroughCity P416 FINISHED
Object Tyumen NE NERFINISHED

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: [European route E22, passesThroughCity, Tyumen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyumen
Context triple: [European route E22, passesThroughCity, 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. Nizhnevartovsk
    Nizhnevartovsk is a major oil-producing city in western Siberia, Russia, known as one of the centers of the country’s petroleum industry.
  • C. 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.
  • D. Tobolsk
    Tobolsk is a historic Siberian town in Russia known for its Kremlin and as a place of exile and imprisonment during the late imperial period.
  • E. Ханты-Мансийск
    Ханты-Мансийск — административный центр Ханты-Мансийского автономного округа — Югры в России, известный как крупный нефтегазовый и спортивный (в частности биатлонный) центр Западной Сибири.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51b90788190a4dd823d962626da completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7ab5177dc8190b888351e9a45b45f completed April 21, 2026, 4:52 p.m.
Created at: April 16, 2026, 4:42 p.m.