Triple

T16707849
Position Surface form Disambiguated ID Type / Status
Subject Tomsk Oblast E406019 entity
Predicate administrative center P1474 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: [Tomsk Oblast, administrative center, Tomsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tomsk
Context triple: [Tomsk Oblast, administrative center, 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38337ecac8190bc4a9410ed7681ab completed April 18, 2026, 1:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a015fb40dc08190b9d6a04f3c19f57d completed May 11, 2026, 4:48 a.m.
Created at: April 10, 2026, 5:20 a.m.