Triple

T23131934
Position Surface form Disambiguated ID Type / Status
Subject Penza Oblast E577191 entity
Predicate hasCity P316 FINISHED
Object Zarechny
Zarechny is a small Russian city in Penza Oblast known for its origins as a closed town associated with the nuclear industry.
E1571493 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: Zarechny | Statement: [Penza Oblast, hasCity, Zarechny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zarechny
Context triple: [Penza Oblast, hasCity, Zarechny]
  • A. Zarechny
    Zarechny is a small Russian city in Sverdlovsk Oblast known for its role in the region’s industrial and energy sectors.
  • B. Malyovitsa
    Malyovitsa is a prominent peak in Bulgaria renowned for its rugged alpine scenery and popularity among climbers and hikers.
  • C. Rechitsa
    Rechitsa is a historic town in southeastern Belarus, situated on the Dnieper River and known as one of the country’s oldest settlements.
  • D. Shakhty
    Shakhty is an industrial city in southwestern Russia known historically for its coal mining and located within Rostov Oblast.
  • E. Chertanovskaya
    Chertanovskaya is a Moscow Metro station serving the Chertanovo district in the city’s south.
  • 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: Zarechny
Triple: [Penza Oblast, hasCity, Zarechny]
Generated description
Zarechny is a small Russian city in Penza Oblast known for its origins as a closed town associated with the nuclear industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zarechny
Target entity description: Zarechny is a small Russian city in Penza Oblast known for its origins as a closed town associated with the nuclear industry.
  • A. Zarechny
    Zarechny is a small Russian city in Sverdlovsk Oblast known for its role in the region’s industrial and energy sectors.
  • B. Malyovitsa
    Malyovitsa is a prominent peak in Bulgaria renowned for its rugged alpine scenery and popularity among climbers and hikers.
  • C. Rechitsa
    Rechitsa is a historic town in southeastern Belarus, situated on the Dnieper River and known as one of the country’s oldest settlements.
  • D. Shakhty
    Shakhty is an industrial city in southwestern Russia known historically for its coal mining and located within Rostov Oblast.
  • E. Chertanovskaya
    Chertanovskaya is a Moscow Metro station serving the Chertanovo district in the city’s south.
  • 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_69e245f7b0e481909c473ff4e6a54e2c completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e88909881908c695cd7d39d380c completed April 29, 2026, 4:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c23f7dccc8190aaba967e73cc6892 completed May 19, 2026, 8:48 a.m.
NEDg Description generation batch_6a0c28ed782c8190a60cf2212a1e7861 completed May 19, 2026, 9:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0c29bca4c08190a29d4204c75b333f completed May 19, 2026, 9:13 a.m.
Created at: April 17, 2026, 4 p.m.