Triple

T9398539
Position Surface form Disambiguated ID Type / Status
Subject Tyumen Oblast E226406 entity
Predicate hasCity P316 FINISHED
Object Yalutorovsk
Yalutorovsk is a historic town in western Siberia, Russia, known for its 17th-century origins as a fortress settlement and its location on the Tobol River.
 E824138 NE FINISHED

How this triple was built (4 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: Yalutorovsk | Statement: [Tyumen Oblast, hasCity, Yalutorovsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yalutorovsk
Context triple: [Tyumen Oblast, hasCity, Yalutorovsk]
  • A. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • B. Makeyevka
    Makeyevka is an industrial city in eastern Ukraine’s Donetsk Oblast, historically known for its coal mining and metallurgical industries.
  • C. Petrovskoye
    Petrovskoye was the original Russian fortress settlement that later developed into the modern city of Makhachkala in Dagestan, Russia.
  • D. Yelizovo
    Yelizovo is a town on Russia’s Kamchatka Peninsula that functions as a key regional hub and gateway to the area’s volcanic and natural attractions.
  • E. Kamyshlov
    Kamyshlov is a small historic town in Russia’s Ural region, known for its traditional wooden architecture and role as a local administrative and cultural center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Yalutorovsk
Triple: [Tyumen Oblast, hasCity, Yalutorovsk]
Generated description
Yalutorovsk is a historic town in western Siberia, Russia, known for its 17th-century origins as a fortress settlement and its location on the Tobol River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yalutorovsk
Target entity description: Yalutorovsk is a historic town in western Siberia, Russia, known for its 17th-century origins as a fortress settlement and its location on the Tobol River.
  • A. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • B. Makeyevka
    Makeyevka is an industrial city in eastern Ukraine’s Donetsk Oblast, historically known for its coal mining and metallurgical industries.
  • C. Petrovskoye
    Petrovskoye was the original Russian fortress settlement that later developed into the modern city of Makhachkala in Dagestan, Russia.
  • D. Yelizovo
    Yelizovo is a town on Russia’s Kamchatka Peninsula that functions as a key regional hub and gateway to the area’s volcanic and natural attractions.
  • E. Kamyshlov
    Kamyshlov is a small historic town in Russia’s Ural region, known for its traditional wooden architecture and role as a local administrative and cultural center.
  • F. None of above. chosen

Provenance (5 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_69ca843170f88190800a8ab2b5fc568e completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd51556fc08190b8ff8190a1485a3a completed April 1, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1d59186308190b12c95d24f8486e6 completed April 5, 2026, 3:22 a.m.
NEDg Description generation batch_69d1d6917f0081908b2c82a826873faf completed April 5, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69d1d73452b48190ac3a0d6498a9a641 completed April 5, 2026, 3:29 a.m.
Created at: March 30, 2026, 7:46 p.m.