Triple

T19531205
Position Surface form Disambiguated ID Type / Status
Subject E22 European route E488655 entity
Predicate passesThrough P225 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: [E22 European route, passesThrough, Tyumen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tyumen
Context triple: [E22 European route, passesThrough, 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6363fd1f8819080805346efad2579 completed April 20, 2026, 2:20 p.m.
Created at: April 10, 2026, 1:41 p.m.