Triple

T17295554
Position Surface form Disambiguated ID Type / Status
Subject Chelyabinsk Oblast E419900 entity
Predicate hasCity P316 FINISHED
Object Yuzhnouralsk
Yuzhnouralsk is a small industrial city in Russia’s Ural region, known for its energy and manufacturing enterprises.
E1327118 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: Yuzhnouralsk | Statement: [Chelyabinsk Oblast, hasCity, Yuzhnouralsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yuzhnouralsk
Context triple: [Chelyabinsk Oblast, hasCity, Yuzhnouralsk]
  • A. Novokuznetsk
    Novokuznetsk is a major industrial city in southwestern Siberia, Russia, known for its large metallurgical and coal-mining industries.
  • B. Novokuznetskaya
    Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
  • C. Kuznetsk
    Kuznetsk is a city in Penza Oblast, Russia, known as an industrial and transport center in the Volga region.
  • D. Nizhnekamsk
    Nizhnekamsk is a major industrial city in Russia known for its large petrochemical and oil refining complexes.
  • E. Zheleznogorsk-Ilimsky
    Zheleznogorsk-Ilimsky is a small industrial town in Russia known for its mining and forestry-related industries.
  • 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: Yuzhnouralsk
Triple: [Chelyabinsk Oblast, hasCity, Yuzhnouralsk]
Generated description
Yuzhnouralsk is a small industrial city in Russia’s Ural region, known for its energy and manufacturing enterprises.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Yuzhnouralsk
Target entity description: Yuzhnouralsk is a small industrial city in Russia’s Ural region, known for its energy and manufacturing enterprises.
  • A. Novokuznetsk
    Novokuznetsk is a major industrial city in southwestern Siberia, Russia, known for its large metallurgical and coal-mining industries.
  • B. Novokuznetskaya
    Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
  • C. Kuznetsk
    Kuznetsk is a city in Penza Oblast, Russia, known as an industrial and transport center in the Volga region.
  • D. Nizhnekamsk
    Nizhnekamsk is a major industrial city in Russia known for its large petrochemical and oil refining complexes.
  • E. Zheleznogorsk-Ilimsky
    Zheleznogorsk-Ilimsky is a small industrial town in Russia known for its mining and forestry-related industries.
  • 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e437875b208190bcf0df2ded546257 completed April 19, 2026, 2:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a047123a0408190b03850b3a8942e87 completed May 13, 2026, 12:40 p.m.
NEDg Description generation batch_6a047216091081908e259a5f9d4c8d49 completed May 13, 2026, 12:44 p.m.
NED2 Entity disambiguation (via description) batch_6a0472a5bec08190849a64fc2fce18e8 completed May 13, 2026, 12:46 p.m.
Created at: April 10, 2026, 5:40 a.m.