Triple

T4632066
Position Surface form Disambiguated ID Type / Status
Subject Sergei Bobrovsky E101439 entity
Predicate placeOfBirth P1 FINISHED
Object Novokuznetsk
Novokuznetsk is a major industrial city in southwestern Siberia, Russia, known for its large metallurgical and coal-mining industries.
 E527378 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: Novokuznetsk | Statement: [Sergei Bobrovsky, placeOfBirth, Novokuznetsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Novokuznetsk
Context triple: [Sergei Bobrovsky, placeOfBirth, Novokuznetsk]
  • A. Novokuznetskaya
    Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
  • B. 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.
  • C. Nizhnekamsk
    Nizhnekamsk is a major industrial city in Russia known for its large petrochemical and oil refining complexes.
  • D. Barnaul
    Barnaul is a significant industrial and cultural city in southwestern Siberia, Russia, located near the Ob River and serving as a key regional center.
  • E. 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.
  • 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: Novokuznetsk
Triple: [Sergei Bobrovsky, placeOfBirth, Novokuznetsk]
Generated description
Novokuznetsk is a major industrial city in southwestern Siberia, Russia, known for its large metallurgical and coal-mining industries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Novokuznetsk
Target entity description: Novokuznetsk is a major industrial city in southwestern Siberia, Russia, known for its large metallurgical and coal-mining industries.
  • A. Novokuznetskaya
    Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
  • B. 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.
  • C. Nizhnekamsk
    Nizhnekamsk is a major industrial city in Russia known for its large petrochemical and oil refining complexes.
  • D. Barnaul
    Barnaul is a significant industrial and cultural city in southwestern Siberia, Russia, located near the Ob River and serving as a key regional center.
  • E. 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.
  • 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_69bd43d2f1c081908cd4b7ec48ecc73d completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a342ffc8190a911d0598ed230bb completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfe61a2cd8819089ea67309d284be4 completed March 22, 2026, 12:52 p.m.
NEDg Description generation batch_69bfe686b99881908bb9a952d5c120c9 completed March 22, 2026, 12:54 p.m.
NED2 Entity disambiguation (via description) batch_69bfe6e8d18c8190a676e59cd16d6b12 completed March 22, 2026, 12:56 p.m.
Created at: March 20, 2026, 1:13 p.m.