Triple

T12440243
Position Surface form Disambiguated ID Type / Status
Subject Krasnoyarsk Time E297249 entity
Predicate usedInCity P4810 FINISHED
Object Tomsk E208233 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: Tomsk | Statement: [Krasnoyarsk Time, usedInCity, Tomsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomsk
Context triple: [Krasnoyarsk Time, usedInCity, Tomsk]
  • A. Tomsk chosen
    Tomsk is a historic university and research city in southwestern Siberia, known as one of the region’s oldest and most important cultural and educational centers.
  • 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. 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. Neftekamsk
    Neftekamsk is an industrial city in the Republic of Bashkortostan, Russia, known for its oil-related industries and vehicle manufacturing.
  • 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_69d6ada166c48190b902972cd2408fa3 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8ecb6c8190a19cbf9de31cabbd completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fef6c34481909e18bce1154e7146 completed May 3, 2026, 7:53 a.m.
Created at: April 8, 2026, 9:55 p.m.